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ORCIDAndries P. Engelbrecht
Andries Petrus Engelbrecht
Person information
- affiliation: University of Stellenbosch, Computer Science Division, South Africa
- affiliation: University of Pretoria, Department of Computer Science, South Africa
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Books and Theses
- 2007
[b3]Andries P. Engelbrecht:
Computational Intelligence: An Introduction, Second Edition. Wiley 2007, ISBN 978-0-470-03561-0, pp. I-XXX, 1-597- 2005
- [b2]Andries P. Engelbrecht:
Fundamentals of Computational Swarm Intelligence. Wiley 2005, ISBN 978-0-470-09191-3, pp. I-XXXV, 1-599 - 2002
- [b1]Andries P. Engelbrecht:
Computational Intelligence: An Introduction. Wiley 2002, ISBN 978-0-47051251-7
Journal Articles
- 2024
- [j112]Mathys Ellis, Anna S. Bosman, Andries P. Engelbrecht:
Regularised feed forward neural networks for streamed data classification problems. Eng. Appl. Artif. Intell. 133: 108555 (2024) - [j111]Daniel H. Von Eschwege, Andries P. Engelbrecht:
Belief space-guided approach to self-adaptive particle swarm optimization. Swarm Intell. 18(1): 31-78 (2024) - 2023
- [j110]Kyle Erwin
, Andries P. Engelbrecht:
Multi-Guide Set-Based Particle Swarm Optimization for Multi-Objective Portfolio Optimization. Algorithms 16(2): 62 (2023) - [j109]Christiaan Scheepers, Andries P. Engelbrecht:
The Porcupine Measure for Comparing the Performance of Multi-Objective Optimization Algorithms. Algorithms 16(6): 283 (2023) - [j108]Kyle Erwin, Andries P. Engelbrecht:
Feature-Based Complexity Measure for Multinomial Classification Datasets. Entropy 25(7): 1000 (2023) - [j107]Kyle Erwin, Andries P. Engelbrecht:
Meta-heuristics for portfolio optimization. Soft Comput. 27(24): 19045-19073 (2023) - [j106]Amirali Madani, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Cooperative coevolutionary multi-guide particle swarm optimization algorithm for large-scale multi-objective optimization problems. Swarm Evol. Comput. 78: 101262 (2023) - 2022
- [j105]Andries P. Engelbrecht, Phlippie Bosman, Katherine M. Malan:
The influence of fitness landscape characteristics on particle swarm optimisers. Nat. Comput. 21(2): 335-345 (2022) - [j104]Pawel Jocko, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Multi-guide particle swarm optimisation archive management strategies for dynamic optimisation problems. Swarm Intell. 16(2): 143-168 (2022) - 2021
- [j103]Jonathan Mwaura, Andries P. Engelbrecht, Filipe V. Nepomuceno:
Diversity Measures for Niching Algorithms. Algorithms 14(2): 36 (2021) - [j102]Ryan Dieter Lang, Andries P. Engelbrecht:
An Exploratory Landscape Analysis-Based Benchmark Suite. Algorithms 14(3): 78 (2021) - [j101]Werner Mostert, Katherine M. Malan, Andries P. Engelbrecht:
A Feature Selection Algorithm Performance Metric for Comparative Analysis. Algorithms 14(3): 100 (2021) - [j100]Cody Dennis, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
An analysis of the impact of subsampling on the neural network error surface. Neurocomputing 466: 252-264 (2021) - [j99]Mathys Ellis, Anna S. Bosman, Andries P. Engelbrecht:
Characterisation of environment type and difficulty for streamed data classification problems. Inf. Sci. 569: 615-649 (2021) - [j98]Salihu A. Abdulkarim, Andries P. Engelbrecht:
Time series forecasting with feedforward neural networks trained using particle swarm optimizers for dynamic environments. Neural Comput. Appl. 33(7): 2667-2683 (2021) - [j97]Stéfan A. G. van der Stockt, Gary Pamparà, Andries P. Engelbrecht, Christopher W. Cleghorn:
Performance analysis of dynamic optimization algorithms using relative error distance. Swarm Evol. Comput. 66: 100930 (2021) - [j96]Cian Steenkamp, Andries P. Engelbrecht:
A scalability study of the multi-guide particle swarm optimization algorithm to many-objectives. Swarm Evol. Comput. 66: 100943 (2021) - 2020
- [j95]David Chushig-Muzo, Cristina Soguero-Ruíz, Andries P. Engelbrecht, Pablo de Miguel-Bohoyo, Inmaculada Mora-Jiménez:
Data-Driven Visual Characterization of Patient Health-Status Using Electronic Health Records and Self-Organizing Maps. IEEE Access 8: 137019-137031 (2020) - [j94]Andreas Kamilaris, Andries P. Engelbrecht, Andreas Pitsillides, Francesc X. Prenafeta-Boldú:
Transfer of manure as fertilizer from livestock farms to crop fields: The case of Catalonia. Comput. Electron. Agric. 175: 105550 (2020) - [j93]Shubham Gupta, Kusum Deep, Andries P. Engelbrecht:
A memory guided sine cosine algorithm for global optimization. Eng. Appl. Artif. Intell. 93: 103718 (2020) - [j92]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Visualising basins of attraction for the cross-entropy and the squared error neural network loss functions. Neurocomputing 400: 113-136 (2020) - [j91]Elre T. Oldewage, Andries P. Engelbrecht, Christopher W. Cleghorn:
Movement patterns of a particle swarm in high dimensional spaces. Inf. Sci. 512: 1043-1062 (2020) - [j90]Cody Dennis, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Random Regrouping and Factorization in Cooperative Particle Swarm Optimization Based Large-Scale Neural Network Training. Neural Process. Lett. 51(1): 759-796 (2020) - [j89]Cody Dennis, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
An Analysis of Activation Function Saturation in Particle Swarm Optimization Trained Neural Networks. Neural Process. Lett. 52(2): 1123-1153 (2020) - 2019
- [j88]Andries P. Engelbrecht, Jacomine Grobler, Joost Langeveld:
Set based particle swarm optimization for the feature selection problem. Eng. Appl. Artif. Intell. 85: 324-336 (2019) - [j87]Mpho C. Nkosi, Lusani Mamushiane, Albert A. Lysko, David L. Johnson, Andries P. Engelbrecht:
Towards programmable on-demand lightpath services: current state-of-the-art and open research areas. IET Networks 8(6): 347-355 (2019) - [j86]Jason F. Nicholls, Andries P. Engelbrecht:
Co-evolved genetic programs for stock market trading. Intell. Syst. Account. Finance Manag. 26(3): 117-136 (2019) - [j85]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
A parameter-free particle swarm optimization algorithm using performance classifiers. Inf. Sci. 503: 381-400 (2019) - [j84]Salihu A. Abdulkarim, Andries P. Engelbrecht:
Time Series Forecasting Using Neural Networks: Are Recurrent Connections Necessary? Neural Process. Lett. 50(3): 2763-2795 (2019) - [j83]Elre T. Oldewage, Andries P. Engelbrecht, Christopher W. Cleghorn:
Degrees of stochasticity in particle swarm optimization. Swarm Intell. 13(3-4): 193-215 (2019) - [j82]Christiaan Scheepers, Andries P. Engelbrecht, Christopher W. Cleghorn:
Multi-guide particle swarm optimization for multi-objective optimization: empirical and stability analysis. Swarm Intell. 13(3-4): 245-276 (2019) - 2018
- [j81]Anna S. Bosman, Andries P. Engelbrecht, Mardé Helbig:
Fitness Landscape Analysis of Weight-Elimination Neural Networks. Neural Process. Lett. 48(1): 353-373 (2018) - [j80]Jacomine Grobler, Andries P. Engelbrecht:
Arithmetic and parent-centric headless chicken crossover operators for dynamic particle swarm optimization algorithms. Soft Comput. 22(18): 5965-5976 (2018) - [j79]Christopher Wesley Cleghorn, Andries P. Engelbrecht:
Particle swarm stability: a theoretical extension using the non-stagnate distribution assumption. Swarm Intell. 12(1): 1-22 (2018) - [j78]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Self-adaptive particle swarm optimization: a review and analysis of convergence. Swarm Intell. 12(3): 187-226 (2018) - [j77]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Optimal parameter regions and the time-dependence of control parameter values for the particle swarm optimization algorithm. Swarm Evol. Comput. 41: 20-35 (2018) - [j76]Stefan van der Stockt, Andries P. Engelbrecht:
Analysis of selection hyper-heuristics for population-based meta-heuristics in real-valued dynamic optimization. Swarm Evol. Comput. 43: 127-146 (2018) - [j75]Justin Maltese, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
A Scalability Study of Many-Objective Optimization Algorithms. IEEE Trans. Evol. Comput. 22(1): 79-96 (2018) - 2017
- [j74]Xiaodong Li, Michael G. Epitropakis, Kalyanmoy Deb, Andries P. Engelbrecht:
Seeking Multiple Solutions: An Updated Survey on Niching Methods and Their Applications. IEEE Trans. Evol. Comput. 21(4): 518-538 (2017) - [j73]Christoph F. Stallmann, Andries P. Engelbrecht:
Gramophone Noise Detection and Reconstruction Using Time Delay Artificial Neural Networks. IEEE Trans. Syst. Man Cybern. Syst. 47(6): 893-905 (2017) - 2016
- [j72]Andries P. Engelbrecht:
Particle swarm optimization with crossover: a review and empirical analysis. Artif. Intell. Rev. 45(2): 131-165 (2016) - [j71]Mohammed A. Mohiuddin, Salman A. Khan, Andries P. Engelbrecht:
Fuzzy particle swarm optimization algorithms for the open shortest path first weight setting problem. Appl. Intell. 45(3): 598-621 (2016) - [j70]Christiaan Scheepers, Andries P. Engelbrecht:
Training multi-agent teams from zero knowledge with the competitive coevolutionary team-based particle swarm optimiser. Soft Comput. 20(2): 607-620 (2016) - [j69]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Inertia weight control strategies for particle swarm optimization - Too much momentum, not enough analysis. Swarm Intell. 10(4): 267-305 (2016) - [j68]Haibo He, Nitesh V. Chawla, Huanhuan Chen, Yoonsuck Choe, Andries P. Engelbrecht, Jaya deva, Lyle N. Long, Ali A. Minai, Feiping Nie, Umut Ozertem, Barak A. Pearlmutter, Ling Shao, Jennie Si, Jochen J. Steil, Brijesh K. Verma, Ding Wang:
Editorial IEEE Transactions on Neural Networks and Learning Systems 2016 and Beyond. IEEE Trans. Neural Networks Learn. Syst. 27(1): 1-7 (2016) - 2015
- [j67]Jacomine Grobler, Andries P. Engelbrecht, Graham Kendall, Venkata S. S. Yadavalli:
Heuristic space diversity control for improved meta-hyper-heuristic performance. Inf. Sci. 300: 49-62 (2015) - [j66]Christopher Wesley Cleghorn, Andries P. Engelbrecht:
Particle swarm variants: standardized convergence analysis. Swarm Intell. 9(2-3): 177-203 (2015) - [j65]Barend J. Leonard, Andries P. Engelbrecht, Christopher Wesley Cleghorn:
Critical considerations on angle modulated particle swarm optimisers. Swarm Intell. 9(4): 291-314 (2015) - [j64]Antoine S. D. Dymond, Andries P. Engelbrecht, Schalk Kok, P. Stephan Heyns:
Tuning Optimization Algorithms Under Multiple Objective Function Evaluation Budgets. IEEE Trans. Evol. Comput. 19(3): 341-358 (2015) - 2014
- [j63]Mohammed A. Mohiuddin, Salman A. Khan, Andries P. Engelbrecht:
Simulated evolution and simulated annealing algorithms for solving multi-objective open shortest path first weight setting problem. Appl. Intell. 41(2): 348-365 (2014) - [j62]Mardé Helbig, Andries P. Engelbrecht:
Benchmarks for dynamic multi-objective optimisation algorithms. ACM Comput. Surv. 46(3): 37:1-37:39 (2014) - [j61]Christopher Wesley Cleghorn, Andries P. Engelbrecht:
A generalized theoretical deterministic particle swarm model. Swarm Intell. 8(1): 35-59 (2014) - [j60]Katherine M. Malan, Andries P. Engelbrecht:
Characterising the searchability of continuous optimisation problems for PSO. Swarm Intell. 8(4): 275-302 (2014) - [j59]Mardé Helbig, Andries P. Engelbrecht:
Population-based metaheuristics for continuous boundary-constrained dynamic multi-objective optimisation problems. Swarm Evol. Comput. 14: 31-47 (2014) - 2013
- [j58]Pavlos Antoniou, Andreas Pitsillides, Tim Blackwell, Andries P. Engelbrecht, Loizos Michael:
Congestion control in wireless sensor networks based on bird flocking behavior. Comput. Networks 57(5): 1167-1191 (2013) - [j57]Mario Poggiolini, Andries P. Engelbrecht:
Application of the feature-detection rule to the Negative Selection Algorithm. Expert Syst. Appl. 40(8): 3001-3014 (2013) - [j56]Patricia E. N. Lutu, Andries P. Engelbrecht:
Base Model Combination Algorithm for Resolving Tied Predictions for K-Nearest Neighbor OVA Ensemble Models. INFORMS J. Comput. 25(3): 517-526 (2013) - [j55]Patricia E. N. Lutu, Andries P. Engelbrecht:
Positive-versus-Negative Classification for Model Aggregation in Predictive Data Mining. INFORMS J. Comput. 25(4): 792-807 (2013) - [j54]Katherine M. Malan, Andries P. Engelbrecht:
A survey of techniques for characterising fitness landscapes and some possible ways forward. Inf. Sci. 241: 148-163 (2013) - [j53]Mardé Helbig, Andries P. Engelbrecht:
Performance measures for dynamic multi-objective optimisation algorithms. Inf. Sci. 250: 61-81 (2013) - [j52]Mathys C. du Plessis, Andries P. Engelbrecht:
Differential evolution for dynamic environments with unknown numbers of optima. J. Glob. Optim. 55(1): 73-99 (2013) - [j51]Marco Dorigo, Mauro Birattari, Christian Blum, Anders Lyhne Christensen, Andries P. Engelbrecht, Roderich Groß, Thomas Stützle:
ANTS 2012 special issue - Editorial. Swarm Intell. 7(2-3): 79-81 (2013) - 2012
- [j50]Salman A. Khan, Andries P. Engelbrecht:
A fuzzy particle swarm optimization algorithm for computer communication network topology design. Appl. Intell. 36(1): 161-177 (2012) - [j49]Mathys C. du Plessis, Andries P. Engelbrecht:
Using Competitive Population Evaluation in a differential evolution algorithm for dynamic environments. Eur. J. Oper. Res. 218(1): 7-20 (2012) - [j48]Patricia E. N. Lutu, Andries P. Engelbrecht:
Using OVA modeling to improve classification performance for large datasets. Expert Syst. Appl. 39(4): 4358-4376 (2012) - [j47]Zuwairie Ibrahim, Noor Khafifah Khalid, Jameel Abdulla, Ahmed Mukred, Salinda Buyamin, Zulkifli Md. Yusof, Muhammad Faiz Mohamed Saaid, Norrima Mokhtar, Andries P. Engelbrecht:
A DNA Sequence Design for DNA Computation Based on Binary Vector Evaluated Particle Swarm Optimization. Int. J. Unconv. Comput. 8(2): 119-137 (2012) - [j46]A. J. Graaff, Andries P. Engelbrecht:
Clustering data in stationary environments with a local network neighborhood artificial immune system. Int. J. Mach. Learn. Cybern. 3(1): 1-26 (2012) - [j45]Anna S. Rakitianskaia, Andries P. Engelbrecht:
Training feedforward neural networks with dynamic particle swarm optimisation. Swarm Intell. 6(3): 233-270 (2012) - [j44]Joost Langeveld, Andries P. Engelbrecht:
Set-based particle swarm optimization applied to the multidimensional knapsack problem. Swarm Intell. 6(4): 297-342 (2012) - 2011
- [j43]Wiehann Matthysen, Andries P. Engelbrecht:
A polar coordinate particle swarm optimiser. Appl. Soft Comput. 11(1): 1322-1339 (2011) - [j42]A. J. Graaff, Andries P. Engelbrecht:
Using sequential deviation to dynamically determine the number of clusters found by a local network neighbourhood artificial immune system. Appl. Soft Comput. 11(2): 2698-2713 (2011) - [j41]A. L. Louis, Andries P. Engelbrecht:
Unsupervised discovery of relations for analysis of textual data. Digit. Investig. 7(3-4): 154-171 (2011) - [j40]A. J. Graaff, Andries P. Engelbrecht:
Clustering data in an uncertain environment using an artificial immune system. Pattern Recognit. Lett. 32(2): 342-351 (2011) - [j39]Marco Dorigo, Mauro Birattari, Gianni Di Caro, René Doursat, Andries P. Engelbrecht, Luca Maria Gambardella, Roderich Groß, Erol Sahin, Thomas Stützle:
ANTS 2010 special issue - Editorial. Swarm Intell. 5(3-4): 143-147 (2011) - 2010
- [j38]Jacomine Grobler, Andries P. Engelbrecht, Schalk Kok, Sarma Yadavalli:
Metaheuristics for the multi-objective FJSP with sequence-dependent set-up times, auxiliary resources and machine down time. Ann. Oper. Res. 180(1): 165-196 (2010) - [j37]Patricia E. N. Lutu, Andries P. Engelbrecht:
A decision rule-based method for feature selection in predictive data mining. Expert Syst. Appl. 37(1): 602-609 (2010) - [j36]Frans van den Bergh, Andries Petrus Engelbrecht:
A Convergence Proof for the Particle Swarm Optimiser. Fundam. Informaticae 105(4): 341-374 (2010) - [j35]Isabella Lona Schoeman, Andries P. Engelbrecht:
A novel particle swarm niching technique based on extensive vector operations. Nat. Comput. 9(3): 683-701 (2010) - 2009
- [j34]Mahamed G. H. Omran, Andries P. Engelbrecht, Ayed A. Salman:
Bare bones differential evolution. Eur. J. Oper. Res. 196(1): 128-139 (2009) - [j33]Salman A. Khan, Andries P. Engelbrecht:
Fuzzy hybrid simulated annealing algorithms for topology design of switched local area networks. Soft Comput. 13(1): 45-61 (2009) - [j32]Riccardo Poli, Andries P. Engelbrecht, James Kennedy:
Editorial for the special issue on Particle Swarm Optimization. Swarm Intell. 3(4): 243-244 (2009) - [j31]Andries P. Engelbrecht, Xiaodong Li, Martin Middendorf, Luca Maria Gambardella:
Editorial Special Issue: Swarm Intelligence. IEEE Trans. Evol. Comput. 13(4): 677-680 (2009) - 2008
- [j30]Gavin Potgieter, Andries P. Engelbrecht:
Evolving model trees for mining data sets with continuous-valued classes. Expert Syst. Appl. 35(4): 1513-1532 (2008) - [j29]Daniel Rodic, Andries P. Engelbrecht:
Social networks in simulated multi-robot environment. Int. J. Intell. Comput. Cybern. 1(1): 110-127 (2008) - [j28]Marco Dorigo, Marco Antonio Montes de Oca, Andries P. Engelbrecht:
Particle swarm optimization. Scholarpedia 3(11): 1486 (2008) - 2007
- [j27]Gavin Potgieter, Andries P. Engelbrecht:
Genetic algorithms for the structural optimisation of learned polynomial expressions. Appl. Math. Comput. 186(2): 1441-1466 (2007) - [j26]R. Brits, Andries P. Engelbrecht, Frans van den Bergh:
Locating multiple optima using particle swarm optimization. Appl. Math. Comput. 189(2): 1859-1883 (2007) - [j25]Patricia E. N. Lutu, Andries P. Engelbrecht:
A Comparative study of sample selection methods for classification. ARIMA J. 6: 6 (2007) - [j24]Ayed A. Salman, Andries P. Engelbrecht, Mahamed G. H. Omran:
Empirical analysis of self-adaptive differential evolution. Eur. J. Oper. Res. 183(2): 785-804 (2007) - [j23]Ulrich Paquet, Andries P. Engelbrecht:
Particle Swarms for Linearly Constrained Optimisation. Fundam. Informaticae 76(1-2): 147-170 (2007) - [j22]Mahamed G. H. Omran, Andries P. Engelbrecht, Ayed A. Salman:
An overview of clustering methods. Intell. Data Anal. 11(6): 583-605 (2007) - [j21]Salman A. Khan, Andries P. Engelbrecht:
A new fuzzy operator and its application to topology design of distributed local area networks. Inf. Sci. 177(13): 2692-2711 (2007) - 2006
- [j20]Frans van den Bergh, Andries P. Engelbrecht:
A study of particle swarm optimization particle trajectories. Inf. Sci. 176(8): 937-971 (2006) - [j19]Mahamed G. H. Omran, Ayed A. Salman, Andries P. Engelbrecht:
Dynamic clustering using particle swarm optimization with application in image segmentation. Pattern Anal. Appl. 8(4): 332-344 (2006) - [j18]Patricia E. N. Lutu, Andries P. Engelbrecht:
A comparative study of sample selection methods for classification. South Afr. Comput. J. 36: 69-85 (2006) - 2005
- [j17]Mahamed G. H. Omran, Andries P. Engelbrecht, Ayed A. Salman:
Particle swarm optimization method for image clustering. Int. J. Pattern Recognit. Artif. Intell. 19(3): 297-321 (2005) - [j16]Mahamed G. H. Omran, Andries P. Engelbrecht, Ayed A. Salman:
A Color Image Quantization Algorithm Based on Particle Swarm Optimization. Informatica (Slovenia) 29(3): 261-270 (2005) - [j15]Nelis Franken, Andries P. Engelbrecht:
Evolving intelligent game-playing agent. South Afr. Comput. J. 34: 87 (2005) - [j14]Willem H. Duminy, Andries P. Engelbrecht:
Composing linear evaluation functions from observable features. South Afr. Comput. J. 35: 48-58 (2005) - [j13]Nelis Franken, Andries P. Engelbrecht:
Particle swarm optimization approaches to coevolve strategies for the iterated prisoner's dilemma. IEEE Trans. Evol. Comput. 9(6): 562-579 (2005) - 2004
- [j12]Nelis Franken, Andries P. Engelbrecht:
Evolving intelligent game-playing agents. South Afr. Comput. J. 32: 44-52 (2004) - [j11]Daniel Rodic, Andries P. Engelbrecht:
Social networks as a task allocation tool for multi-robot teams. South Afr. Comput. J. 33: 52-66 (2004) - [j10]Frans van den Bergh, Andries P. Engelbrecht:
A Cooperative Approach to Particle Swarm Optimization. IEEE Trans. Evol. Comput. 8(3): 225-239 (2004) - [j9]L. Messerschmidt, Andries P. Engelbrecht:
Learning to Play Games Using a PSO-Based Competitive Learning Approach. IEEE Trans. Evol. Comput. 8(3): 280-288 (2004) - 2002
- [j8]Andries P. Engelbrecht, R. Brits:
Supervised Training Using an Unsupervised Approach to Active Learning. Neural Process. Lett. 15(3): 247-260 (2002) - 2001
- [j7]Andries P. Engelbrecht:
Sensitivity Analysis for Selective Learning by Feedforward Neural Networks. Fundam. Informaticae 45(4): 295-328 (2001) - [j6]Andries P. Engelbrecht:
Sensitivity Analysis for Selective Learning by Feedforward Neural Networks. Fundam. Informaticae 46(3): 219-252 (2001) - [j5]Andries P. Engelbrecht:
A new pruning heuristic based on variance analysis of sensitivity information. IEEE Trans. Neural Networks 12(6): 1386-1399 (2001) - 2000
- [j4]Andries P. Engelbrecht:
Message from the Guest Editor. Int. J. Comput. Syst. Signals 1(1): 3-4 (2000) - [j3]Frans van den Bergh, Andries P. Engelbrecht:
Cooperative learning in neural networks using particle swarm optimizers. South Afr. Comput. J. 26: 84-90 (2000) - [j2]Andries P. Engelbrecht:
Using the Taylor expansion of multilayer feedforward neural networks. South Afr. Comput. J. 26: 181-189 (2000) - 1999
- [j1]Andries P. Engelbrecht:
Sensitivity Analysis for Decision Boundaries. Neural Process. Lett. 10(3): 253-266 (1999)
Conference and Workshop Papers
- 2023
- [c261]Ana Nikolikj, Gjorgjina Cenikj, Gordana Ispirova, Diederick Vermetten, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
Assessing the Generalizability of a Performance Predictive Model. GECCO Companion 2023: 311-314 - [c260]Ryan Dieter Lang, Andries Petrus Engelbrecht:
Performance Analysis of Hybrid Sampling and Meta-heuristics. GECCO Companion 2023: 499-502 - [c259]Lauren Hayward, Andries P. Engelbrecht:
How to Tell a Fish from a Bee: Constructing Meta-Heuristic Search Behaviour Characteristics. GECCO Companion 2023: 1562-1569 - [c258]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Empirical Loss Landscape Analysis of Neural Network Activation Functions. GECCO Companion 2023: 2029-2037 - [c257]Rijk Marius de Wet, Andries P. Engelbrecht:
Set-based Particle Swarm Optimization for Data Clustering: Comparison and Analysis of Control Parameters. ISMSI 2023: 103-110 - [c256]Daniel H. Von Eschwege, Andries P. Engelbrecht:
A Cautionary Note on Poli's Stability Condition for Particle Swarm Optimization. SSCI 2023: 1189-1194 - [c255]Kyle Erwin, Andries P. Engelbrecht:
Meta-heuristics for Portfolio Optimization: Part I - Review of Meta-heuristics. ICSI (2) 2023: 441-452 - [c254]Kyle Erwin, Andries P. Engelbrecht:
Meta-heuristics for Portfolio Optimization: Part II - Empirical Analysis. ICSI (2) 2023: 453-464 - 2022
- [c253]Alanna McNulty, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Decomposition and Merging Co-operative Particle Swarm Optimization with Random Grouping. ANTS Conference 2022: 117-129 - [c252]Weka Steyn, Andries P. Engelbrecht:
Dynamic Spatial Guided Multi-Guide Particle Swarm Optimization Algorithm for Many-Objective Optimization. ANTS Conference 2022: 130-141 - [c251]Andries P. Engelbrecht:
Stability-Guided Particle Swarm Optimization. ANTS Conference 2022: 360-369 - [c250]Pawel Jocko, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Dynamic Multi-objective Optimisation Using Multi-guide Particle Swarm Optimisation. CEC 2022: 1-10 - [c249]Jean-Pierre van Zyl, Andries P. Engelbrecht:
Rule Induction Using Set-Based Particle Swarm Optimisation. CEC 2022: 1-8 - [c248]Gjorgjina Cenikj, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
SELECTOR: selecting a representative benchmark suite for reproducible statistical comparison. GECCO 2022: 620-629 - [c247]Lienke Brown, Andries P. Engelbrecht:
Set-based Particle Swarm Optimization for Data Clustering. ISMSI 2022: 43-49 - [c246]Weka Steyn, Andries P. Engelbrecht:
Stability-Guided Multi-Guide Particle Swarm Optimization. ISMSI 2022: 55-61 - [c245]Donovan Edeling, Andries P. Engelbrecht:
Static Polynomial Approximation Using Set-based Particle Swarm Optimisation. ISMSI 2022: 67-72 - [c244]Liam J. S. McDevitt, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
A Particle Swarm Optimization Decomposition Strategy for Large Scale Global Optimization. SSCI 2022: 1574-1581 - [c243]Mitchell Clark, Beatrice M. Ombuki-Berman, Nicholas Aksamit, Andries P. Engelbrecht:
Cooperative Particle Swarm Optimization Decomposition Methods for Large-scale Optimization. SSCI 2022: 1582-1591 - [c242]Kyle Erwin, Andries P. Engelbrecht:
Improved Hamming Diversity Measure for Set-Based Optimization Algorithms. ICSI (1) 2022: 39-47 - 2021
- [c241]Amirali Madani, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Decision Space Scalability Analysis of Multi-Objective Particle Swarm Optimization Algorithms. CEC 2021: 2179-2186 - [c240]Cody Dennis, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Predicting Particle Swarm Optimization Control Parameters From Fitness Landscape Characteristics. CEC 2021: 2289-2298 - [c239]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Visualizing and Characterizing the Parameter Configuration Landscape of Particle Swarm Optimization using Physical Landform Classification. CEC 2021: 2299-2306 - [c238]Andries P. Engelbrecht, Christopher W. Cleghorn:
Recent advances in particle swarm optimization analysis and understanding 2021. GECCO Companion 2021: 341-368 - [c237]James Faure, Andries P. Engelbrecht:
A Convolutional Neural Network for Dental Panoramic Radiograph Classification. ISMSI 2021: 54-59 - [c236]Stefan van Deventer, Andries P. Engelbrecht:
Learning to Trade from Zero-Knowledge Using Particle Swarm Optimization. IWANN (2) 2021: 183-195 - [c235]James Faure, Andries P. Engelbrecht:
Impacted Tooth Detection in Panoramic Radiographs. IWANN (1) 2021: 525-536 - [c234]Kyle Erwin, Andries P. Engelbrecht:
Set-based Particle Swarm Optimization for Portfolio Optimization with Adaptive Coordinate Descent Weight Optimization. SSCI 2021: 1-8 - [c233]Kyle Erwin, Andries P. Engelbrecht:
A Tuning Free Approach to Multi-guide Particle Swarm Optimization. SSCI 2021: 1-8 - [c232]Timothy G. Carolus, Andries P. Engelbrecht:
Multi-guide Particle Swarm Optimisation Control Parameter Importance in High Dimensional Spaces. ICSI (1) 2021: 185-198 - [c231]Jean-Pierre van Zyl, Andries P. Engelbrecht:
Polynomial Approximation Using Set-Based Particle Swarm Optimization. ICSI (1) 2021: 210-222 - [c230]Tyler Crane, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Two Modified NichePSO Algorithms for Multimodal Optimization. ICSI (1) 2021: 232-243 - 2020
- [c229]Timothy G. Carolus, Andries P. Engelbrecht:
Control Parameter Importance and Sensitivity Analysis of the Multi-Guide Particle Swarm Optimization Algorithm. ANTS Conference 2020: 96-106 - [c228]Heinrich Cilliers, Andries P. Engelbrecht:
Fitting Gaussian Mixture Models Using Cooperative Particle Swarm Optimization. ANTS Conference 2020: 298-305 - [c227]Kyle Erwin, Andries P. Engelbrecht:
Set-Based Particle Swarm Optimization for Portfolio Optimization. ANTS Conference 2020: 333-339 - [c226]Simon Dennis, Andries P. Engelbrecht:
A Review and Empirical Analysis of Particle Swarm optimization Algorithms for Dynamic Multi-Modal optimization. CEC 2020: 1-8 - [c225]Ryan Dieter Lang, Andries P. Engelbrecht:
Decision Space Coverage of Random Walks. CEC 2020: 1-8 - [c224]Stefan van der Stockt, Andries P. Engelbrecht, Christopher W. Cleghorn:
Heuristic Space Diversity Measures for Population-based Hyper-heuristics. CEC 2020: 1-9 - [c223]Ryan Dieter Lang, Andries P. Engelbrecht:
Distributed random walks for fitness landscape analysis. GECCO 2020: 612-619 - [c222]Andries P. Engelbrecht, Christopher W. Cleghorn:
Recent advances in particle swarm optimization analysis and understanding. GECCO Companion 2020: 747-774 - [c221]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Loss Surface Modality of Feed-Forward Neural Network Architectures. IJCNN 2020: 1-8 - [c220]Callum Parton, Andries P. Engelbrecht:
Mixtures of Heterogeneous Experts. ISMSI 2020: 1-7 - [c219]Andries P. Engelbrecht, Mardé Helbig:
Empirical Analysis of A Partial Dominance Approach to Many-Objective Optimisation. ISMSI 2020: 71-75 - [c218]Mardé Helbig, Andries P. Engelbrecht:
Partial Dominance for Many-Objective Optimization. ISMSI 2020: 81-86 - [c217]Reginald McLean, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Swarm Based Algorithms for Neural Network Training. SMC 2020: 2585-2592 - [c216]Simon Dennis, Andries P. Engelbrecht:
Dynamic Multi-Swarm Fractional-best Particle Swarm Optimization for Dynamic Multi-modal Optimization. SSCI 2020: 1549-1556 - [c215]Thorsten Schmidt-Dumont, Andries P. Engelbrecht:
Analysis of Particle Swarm Optimisation for Training Support Vector Machines. SSCI 2020: 1557-1564 - [c214]Kyle Erwin, Andries P. Engelbrecht:
Improved Set-based Particle Swarm optimization for Portfolio optimization. SSCI 2020: 1573-1580 - [c213]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Visualizing and Characterizing the Parameter Configuration Landscape of Differential Evolution using Physical Landform Classification. SSCI 2020: 2437-2444 - 2019
- [c212]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
The Parameter Configuration Landscape: A Case Study on Particle Swarm Optimization. CEC 2019: 808-814 - [c211]Werner Mostert, Katherine M. Malan, Gabriela Ochoa, Andries P. Engelbrecht:
Insights into the Feature Selection Problem Using Local Optima Networks. EvoCOP 2019: 147-162 - [c210]Kyle Erwin, Andries P. Engelbrecht:
Control parameter sensitivity analysis of the multi-guide particle swarm optimization algorithm. GECCO 2019: 22-29 - [c209]Andries P. Engelbrecht, Christopher Wesley Cleghorn:
Recent advances in particle swarm optimization analysis and understanding. GECCO (Companion) 2019: 923-950 - [c208]Gary Pamparà, Andries P. Engelbrecht:
Evolutionary and swarm-intelligence algorithms through monadic composition. GECCO (Companion) 2019: 1382-1390 - [c207]Gary Pamparà, Andries P. Engelbrecht:
A generator for dynamically constrained optimization problems. GECCO (Companion) 2019: 1441-1448 - [c206]Ryan Dieter Lang, Andries P. Engelbrecht:
On the Robustness of Random Walks for Fitness Landscape Analysis. SSCI 2019: 1898-1906 - [c205]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
An Analysis of Control Parameter Importance in the Particle Swarm Optimization Algorithm. ICSI (1) 2019: 93-105 - 2018
- [c204]Gary Pamparà, Andries P. Engelbrecht:
Self-adaptive Quantum Particle Swarm Optimization for Dynamic Environments. ANTS Conference 2018: 163-175 - [c203]Christopher Wesley Cleghorn, Christiaan Scheepers, Andries P. Engelbrecht:
Stability Analysis of the Multi-objective Multi-guided Particle Swarm Optimizer. ANTS Conference 2018: 201-212 - [c202]Elre T. Oldewage, Andries P. Engelbrecht, Christopher Wesley Cleghorn:
The Importance of Component-Wise Stochasticity in Particle Swarm Optimization. ANTS Conference 2018: 264-276 - [c201]Elre T. Oldewage, Andries P. Engelbrecht, Christopher Wesley Cleghorn:
Boundary Constraint Handling Techniques for Particle Swarm Optimization in High Dimensional Problem Spaces. ANTS Conference 2018: 333-341 - [c200]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Gaussian-Valued Particle Swarm Optimization. ANTS Conference 2018: 368-377 - [c199]Andries P. Engelbrecht, Christopher Wesley Cleghorn:
Particle swarm optimization: a guide to effective, misconception free, real world use. GECCO (Companion) 2018: 831-857 - [c198]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Progressive gradient walk for neural network fitness landscape analysis. GECCO (Companion) 2018: 1473-1480 - [c197]Werner Mostert, Katherine M. Malan, Andries P. Engelbrecht:
Filter versus wrapper feature selection based on problem landscape features. GECCO (Companion) 2018: 1489-1496 - [c196]Ntombikayise Banda, Andries P. Engelbrecht:
Multimodal Emotion Recognition using Deep Continuous Conditional Recurrent Neural Fields. IJCNN 2018: 408-413 - 2017
- [c195]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Optimal parameter regions for particle swarm optimization algorithms. CEC 2017: 349-356 - [c194]Christiaan Scheepers, Andries P. Engelbrecht:
Vector evaluated particle swarm optimization: The archive's influence on performance. CEC 2017: 565-572 - [c193]Christopher Wesley Cleghorn, Andries P. Engelbrecht:
Fitness-distance-ratio particle swarm optimization: stability analysis. GECCO 2017: 12-18 - [c192]Jaco Cronje, Andries P. Engelbrecht:
Training Convolutional Neural Networks with Class Based Data Augmentation for Detecting Distracted Drivers. ICCAE 2017: 126-130 - [c191]Ntombikayise Banda, Lang He, Andries P. Engelbrecht:
Bio-acoustic emotion recognition using continuous conditional recurrent neural fields. SSCI 2017: 1-8 - [c190]Christopher Wesley Cleghorn, Andries P. Engelbrecht:
Firefly optimization: A study on frame invariance. SSCI 2017: 1-6 - [c189]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
An adaptive particle swarm optimization algorithm based on optimal parameter regions. SSCI 2017: 1-8 - [c188]Elre T. Oldewage, Andries P. Engelbrecht, Christopher Wesley Cleghorn:
The merits of velocity clamping particle swarm optimisation in high dimensional spaces. SSCI 2017: 1-8 - [c187]Christiaan Scheepers, Andries P. Engelbrecht:
Quantified pareto-optimal front comparisons using attainment surfaces. SSCI 2017: 1-7 - [c186]Jacomine Grobler, Andries P. Engelbrecht:
A Scalability Analysis of Particle Swarm Optimization Roaming Behaviour. ICSI (1) 2017: 119-130 - 2016
- [c185]Andrich B. van Wyk, Andries P. Engelbrecht:
Analysis of activation functions for particle swarm optimised feedforward neural networks. CEC 2016: 423-430 - [c184]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
The sad state of self-adaptive particle swarm optimizers. CEC 2016: 431-439 - [c183]Christopher Wesley Cleghorn, Andries P. Engelbrecht:
Unified particle swarm optimizer: Convergence analysis. CEC 2016: 447-454 - [c182]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
A radius-free quantum particle swarm optimization technique for dynamic optimization problems. CEC 2016: 578-585 - [c181]Mardé Helbig, Kalyanmoy Deb, Andries P. Engelbrecht:
Key challenges and future directions of dynamic multi-objective optimisation. CEC 2016: 1256-1261 - [c180]Christiaan Scheepers, Andries P. Engelbrecht:
Vector evaluated particle swarm optimization exploration behavior part I: Explorative analysis. CEC 2016: 1845-1854 - [c179]Christiaan Scheepers, Andries P. Engelbrecht:
Vector evaluated particle swarm optimization exploration behavior part II: Quantitative analysis. CEC 2016: 1855-1861 - [c178]E. T. van Zyl, Andries P. Engelbrecht:
Group-based stochastic scaling for PSO velocities. CEC 2016: 1862-1868 - [c177]Justin Maltese, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Pareto-based many-objective optimization using knee points. CEC 2016: 3678-3686 - [c176]Jonathan Mwaura, Andries P. Engelbrecht, Filipe V. Nepocumeno:
Performance measures for niching algorithms. CEC 2016: 4775-4784 - [c175]Anna S. Rakitianskaia, Eduan Bekker, Katherine M. Malan, Andries P. Engelbrecht:
Analysis of error landscapes in multi-layered neural networks for classification. CEC 2016: 5270-5277 - [c174]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Search space boundaries in neural network error landscape analysis. SSCI 2016: 1-8 - [c173]Christopher Wesley Cleghorn, Andries P. Engelbrecht:
Particle swarm optimizer: The impact of unstable particles on performance. SSCI 2016: 1-7 - [c172]Willem S. van Heerden, Andries P. Engelbrecht:
An investigation into the effect of unlabeled neurons on Self-Organizing Maps. SSCI 2016: 1-8 - [c171]Christiaan Scheepers, Andries P. Engelbrecht:
Misleading Pareto optimal front diversity metrics: Spacing and distribution. SSCI 2016: 1-8 - [c170]Christiaan Scheepers, Andries P. Engelbrecht:
Vector evaluated particle swarm optimization archive management: Pareto optimal front diversity sensitivity analysis. SSCI 2016: 1-9 - [c169]Jacomine Grobler, Andries P. Engelbrecht:
Hyper-heuristics for the Flexible Job Shop Scheduling Problem with Additional Constraints. ICSI (2) 2016: 3-10 - [c168]Dieter Doman, Mardé Helbig, Andries P. Engelbrecht:
Heterogeneous Vector-Evaluated Particle Swarm Optimisation in Static Environments. ICSI (1) 2016: 293-304 - [c167]Jacomine Grobler, Andries P. Engelbrecht:
Headless Chicken Particle Swarm Optimization Algorithms. ICSI (1) 2016: 350-357 - [c166]Albert Volschenk, Andries P. Engelbrecht:
An Analysis of Competitive Coevolutionary Particle Swarm Optimizers to Train Neural Network Game Tree Evaluation Functions. ICSI (1) 2016: 369-380 - 2015
- [c165]Ntombikayise Banda, Andries P. Engelbrecht, Peter Robinson:
Continuous emotion recognition using a particle swarm optimized NARX neural network. ACII 2015: 380-386 - [c164]Anna S. Rakitianskaia, Andries P. Engelbrecht:
Saturation in PSO neural network training: Good or evil? CEC 2015: 125-132 - [c163]Christopher Wesley Cleghorn, Andries P. Engelbrecht:
Fully informed particle swarm optimizer: Convergence analysis. CEC 2015: 164-170 - [c162]Derek Dibblee, Justin Maltese, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Vector-evaluated particle swarm optimization with local search. CEC 2015: 187-195 - [c161]Stefan van der Stockt, Andries P. Engelbrecht:
Analysis of global information sharing in hyper-heuristics for different dynamic environments. CEC 2015: 822-829 - [c160]Ron Bond, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Evaluating landscape characteristics of dynamic benchmark functions. CEC 2015: 1343-1350 - [c159]Katherine M. Malan, Johannes F. Oberholzer, Andries P. Engelbrecht:
Characterising constrained continuous optimisation problems. CEC 2015: 1351-1358 - [c158]Mardé Helbig, Andries P. Engelbrecht:
Influence of the archive size on the performance of the dynamic vector evaluated particle swarm optimisation algorithm solving dynamic multi-objective optimisation problems. CEC 2015: 1926-1933 - [c157]Mathys C. du Plessis, Andries P. Engelbrecht, André P. Calitz:
Self-Adapting the Brownian Radius in a Differential Evolution Algorithm for Dynamic Environments. FOGA 2015: 114-128 - [c156]Mardé Helbig, Andries P. Engelbrecht:
The Effect of Quantum and Charged Particles on the Performance of the Dynamic Vector-evaluated Particle Swarm Optimisation Algorithm. GECCO 2015: 25-32 - [c155]Andries P. Engelbrecht:
Particle Swarm Optimization. GECCO (Companion) 2015: 65-91 - [c154]Christoph F. Stallmann, Andries P. Engelbrecht:
Signal Modelling for the Digital Reconstruction of Gramophone Noise. ICETE (Selected Papers) 2015: 411-432 - [c153]Mardé Helbig, Andries P. Engelbrecht:
Using Headless Chicken Crossover for Local Guide Selection When Solving Dynamic Multi-objective Optimization. NaBIC 2015: 381-392 - [c152]Christoph F. Stallmann, Andries P. Engelbrecht:
Gramophone Noise Reconstruction - A Comparative Study of Interpolation Algorithms for Noise Reduction. SIGMAP 2015: 31-38 - [c151]Elre Van Zyl, Andries P. Engelbrecht:
A Subspace-Based Method for PSO Initialization. SSCI 2015: 226-233 - [c150]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
The Effect of Probability Distributions on the Performance of Quantum Particle Swarm Optimization for Solving Dynamic Optimization Problems. SSCI 2015: 242-250 - [c149]Barend J. Leonard, Andries P. Engelbrecht:
Frequency Distribution of Candidate Solutions in Angle Modulated Particle Swarms. SSCI 2015: 251-258 - [c148]Ntombikayise Banda, Andries P. Engelbrecht, Peter Robinson:
Feature Reduction for Dimensional Emotion Recognition in Human-Robot Interaction. SSCI 2015: 803-810 - [c147]Mardé Helbig, Andries P. Engelbrecht:
Dynamic Vector-Evaluated PSO with Guaranteed Convergence in the Sub-Swarms. SSCI 2015: 1286-1293 - [c146]Justin Maltese, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Co-operative Vector-Evaluated Particle Swarm Optimization for Multi-objective Optimization. SSCI 2015: 1294-1301 - [c145]Justin Maltese, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
High-Dimensional Multi-Objective Optimization Using Co-operative Vector-Evaluated Particle Swarm Optimization with Random Variable Grouping. SSCI 2015: 1302-1309 - [c144]Anna S. Rakitianskaia, Andries P. Engelbrecht:
Measuring Saturation in Neural Networks. SSCI 2015: 1423-1430 - [c143]Gary Pampara, Andries P. Engelbrecht:
Towards A Generic Computational Intelligence Library: Preventing Insanity. SSCI 2015: 1460-1467 - [c142]Jacomine Grobler, Andries P. Engelbrecht:
Metric-Based Heuristic Space Diversity Management in a Meta-Hyper-Heuristic Framework. SSCI 2015: 1665-1672 - 2014
- [c141]Barend J. Leonard, Andries P. Engelbrecht:
Angle Modulated Particle Swarm Variants. ANTS Conference 2014: 38-49 - [c140]Phlippie Bosman, Andries P. Engelbrecht:
Diversity Rate of Change Measurement for Particle Swarm Optimisers. ANTS Conference 2014: 86-97 - [c139]Christopher Wesley Cleghorn, Andries P. Engelbrecht:
Particle Swarm Convergence: Standardized Analysis and Topological Influence. ANTS Conference 2014: 134-145 - [c138]Jade Z. Abbott, Andries P. Engelbrecht:
Nature-Inspired Swarm Robotics Algorithms for Prioritized Foraging. ANTS Conference 2014: 246-253 - [c137]Kristina S. Georgieva, Andries P. Engelbrecht:
Cooperative DynDE for temporal data clustering. IEEE Congress on Evolutionary Computation 2014: 437-444 - [c136]Christiaan Scheepers, Andries P. Engelbrecht:
Competitive coevolutionary training of simple soccer agents from zero knowledge. IEEE Congress on Evolutionary Computation 2014: 1210-1217 - [c135]Robert W. Garden, Andries P. Engelbrecht:
Analysis and classification of optimisation benchmark functions and benchmark suites. IEEE Congress on Evolutionary Computation 2014: 1641-1649 - [c134]Jacomine Grobler, Andries P. Engelbrecht, Graham Kendall, Venkata S. S. Yadavalli:
Heuristic space diversity management in a meta-hyper-heuristic framework. IEEE Congress on Evolutionary Computation 2014: 1863-1869 - [c133]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Dynamic multi-objective optimization using charged vector evaluated particle swarm optimization. IEEE Congress on Evolutionary Computation 2014: 1929-1936 - [c132]Katherine M. Malan, Andries P. Engelbrecht:
A progressive random walk algorithm for sampling continuous fitness landscapes. IEEE Congress on Evolutionary Computation 2014: 2507-2514 - [c131]Christopher Wesley Cleghorn, Andries P. Engelbrecht:
Particle swarm convergence: An empirical investigation. IEEE Congress on Evolutionary Computation 2014: 2524-2530 - [c130]Ronald Klazar, Andries P. Engelbrecht:
Parameter optimization by means of statistical quality guides in F-Race. IEEE Congress on Evolutionary Computation 2014: 2547-2552 - [c129]Stuart G. Reid, Katherine M. Malan, Andries P. Engelbrecht:
Carry trade portfolio optimization using particle swarm optimization. IEEE Congress on Evolutionary Computation 2014: 3051-3058 - [c128]Mardé Helbig, Andries P. Engelbrecht:
Heterogeneous dynamic vector evaluated particle swarm optimisation for dynamic multi-objective optimisation. IEEE Congress on Evolutionary Computation 2014: 3151-3159 - [c127]Stefan van der Stockt, Andries P. Engelbrecht:
Analysis of hyper-heuristic performance in different dynamic environments. CIDUE 2014: 1-8 - [c126]Jacomine Grobler, Andries P. Engelbrecht, Graham Kendall, Venkata S. S. Yadavalli:
The entity-to-algorithm allocation problem: extending the analysis. CIEL 2014: 54-61 - [c125]Andries P. Engelbrecht:
Particle swarm optimization. GECCO (Companion) 2014: 381-406 - [c124]Anna S. Rakitianskaia, Andries P. Engelbrecht:
Training high-dimensional neural networks with cooperative particle swarm optimiser. IJCNN 2014: 4011-4018 - [c123]Anna S. Rakitianskaia, Andries P. Engelbrecht:
Weight regularisation in particle swarm optimisation neural network training. SIS 2014: 34-41 - [c122]E. T. van Zyl, Andries P. Engelbrecht:
Comparison of self-adaptive particle swarm optimizers. SIS 2014: 48-56 - [c121]Andries P. Engelbrecht:
Asynchronous particle swarm optimization with discrete crossover. SIS 2014: 141-148 - [c120]Katherine M. Malan, Andries P. Engelbrecht:
Particle swarm optimisation failure prediction based on fitness landscape characteristics. SIS 2014: 149-157 - [c119]Andries P. Engelbrecht:
Fitness function evaluations: A fair stopping condition? SIS 2014: 181-188 - [c118]Christiaan Scheepers, Andries P. Engelbrecht:
Analysis of stagnation behaviour of competitive coevolutionary trained neuro-controllers. SIS 2014: 197-204 - [c117]Mardé Helbig, Andries P. Engelbrecht:
Using heterogeneous knowledge sharing strategies with dynamic vector-evaluated particle swarm optimisation. SIS 2014: 259-266 - 2013
- [c116]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
A scalability study of multi-objective particle swarm optimizers. IEEE Congress on Evolutionary Computation 2013: 189-197 - [c115]Filipe V. Nepomuceno, Andries P. Engelbrecht:
A self-adaptive heterogeneous pso for real-parameter optimization. IEEE Congress on Evolutionary Computation 2013: 361-368 - [c114]Jacomine Grobler, Andries P. Engelbrecht, Graham Kendall, Venkata S. S. Yadavalli:
Multi-method algorithms: Investigating the entity-to-algorithm allocation problem. IEEE Congress on Evolutionary Computation 2013: 570-577 - [c113]Katherine M. Malan, Andries P. Engelbrecht:
Ruggedness, funnels and gradients in fitness landscapes and the effect on PSO performance. IEEE Congress on Evolutionary Computation 2013: 963-970 - [c112]Mardé Helbig, Andries P. Engelbrecht:
Analysing the performance of dynamic multi-objective optimisation algorithms. IEEE Congress on Evolutionary Computation 2013: 1531-1539 - [c111]Barend J. Leonard, Andries P. Engelbrecht:
On the optimality of particle swarm parameters in dynamic environments. IEEE Congress on Evolutionary Computation 2013: 1564-1569 - [c110]Kristina Georgieva, Andries P. Engelbrecht:
A cooperative multi-population approach to clustering temporal data. IEEE Congress on Evolutionary Computation 2013: 1983-1991 - [c109]Andries P. Engelbrecht:
Particle swarm optimization with discrete crossover. IEEE Congress on Evolutionary Computation 2013: 2457-2464 - [c108]Mardé Helbig, Andries P. Engelbrecht:
Issues with performance measures for dynamic multi-objective optimisation. CIDUE 2013: 17-24 - [c107]Mardé Helbig, Andries P. Engelbrecht:
Benchmarks for dynamic multi-objective optimisation. CIDUE 2013: 84-91 - [c106]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Knowledge Transfer Strategies for Vector Evaluated Particle Swarm Optimization. EMO 2013: 171-184 - [c105]Katherine M. Malan, Andries P. Engelbrecht:
Steep gradients as a predictor of PSO failure. GECCO (Companion) 2013: 9-10 - [c104]Kristina Georgieva, Andries P. Engelbrecht:
Dynamic Differential Evolution Algorithm for Clustering Temporal Data. LSSC 2013: 240-247 - [c103]Andries P. Engelbrecht:
Fruitless search in differential evolution. SDE 2013: 9-17 - [c102]Wiehann Matthysen, Andries P. Engelbrecht, Katherine M. Malan:
Analysis of stagnation behavior of vector evaluated particle swarm optimization. SIS 2013: 155-163 - [c101]N. J. Unger, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Cooperative particle swarm optimization in dynamic environments. SIS 2013: 172-179 - 2012
- [c100]Adiel Ismail, Andries P. Engelbrecht:
Measuring Diversity in the Cooperative Particle Swarm Optimizer. ANTS 2012: 97-108 - [c99]Barend J. Leonard, Andries P. Engelbrecht:
Scalability Study of Particle Swarm Optimizers in Dynamic Environments. ANTS 2012: 121-132 - [c98]Adiel Ismail, Andries P. Engelbrecht:
The Self-adaptive Comprehensive Learning Particle Swarm Optimizer. ANTS 2012: 156-167 - [c97]Filipe V. Nepomuceno, Andries P. Engelbrecht:
A Self-adaptive Heterogeneous PSO Inspired by Ants. ANTS 2012: 188-195 - [c96]Ronald Klazar, Andries P. Engelbrecht:
Dynamic Load Balancing Inspired by Cemetery Formation in Ant Colonies. ANTS 2012: 236-243 - [c95]Jade Z. Abbott, Andries P. Engelbrecht:
Performance of Bacterial Foraging Optimization in Dynamic Environments. ANTS 2012: 284-291 - [c94]Christopher Wesley Cleghorn, Andries P. Engelbrecht:
Piecewise Linear Approximation of n-Dimensional Parametric Curves Using Particle Swarms. ANTS 2012: 292-299 - [c93]Julien G. O. L. Duhain, Andries P. Engelbrecht:
Towards a more complete classification system for dynamically changing environments. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c92]Andries P. Engelbrecht:
Particle swarm optimization: Velocity initialization. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c91]Jacomine Grobler, Andries P. Engelbrecht, Graham Kendall, Venkata S. S. Yadavalli:
Investigating the use of local search for improving meta-hyper-heuristic performance. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c90]Mardé Helbig, Andries P. Engelbrecht:
Analyses of guide update approaches for vector evaluated particle swarm optimisation on dynamic multi-objective optimisation problems. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c89]Adiel Ismail, Andries P. Engelbrecht:
Self-Adaptive Particle Swarm Optimization. SEAL 2012: 228-237 - [c88]Willem S. van Heerden, Andries P. Engelbrecht:
Unsupervised Weight-Based Cluster Labeling for Self-Organizing Maps. WSOM 2012: 45-54 - 2011
- [c87]Antoine S. D. Dymond, Andries P. Engelbrecht, P. Stephan Heyns:
The sensitivity of single objective optimization algorithm control parameter values under different computational constraints. IEEE Congress on Evolutionary Computation 2011: 1412-1419 - [c86]Mardé Helbig, Andries P. Engelbrecht:
Archive management for dynamic multi-objective optimisation problems using vector evaluated particle swarm optimisation. IEEE Congress on Evolutionary Computation 2011: 2047-2054 - [c85]Jacomine Grobler, Andries P. Engelbrecht, Graham Kendall, Venkata S. S. Yadavalli:
Investigating the impact of alternative evolutionary selection strategies on multi-method global optimization. IEEE Congress on Evolutionary Computation 2011: 2337-2344 - [c84]Evangelos Papacostantis, Andries P. Engelbrecht:
Coevolutionary particle swarm optimization for evolving trend reversal indicators. CIFEr 2011: 27-34 - [c83]Jason F. Nicholls, Katherine M. Malan, Andries P. Engelbrecht:
Comparison of trade decision strategies in an equity market GA trader. CIFEr 2011: 51-58 - [c82]Salman A. Khan, Andries P. Engelbrecht:
Assessment of the "Evaluation" function in the simulated evolution algorithm. ICNC 2011: 1062-1066 - [c81]Pavlos Antoniou, Andreas Pitsillides, Andries P. Engelbrecht, Tim Blackwell, Loizos Michael:
Applying swarm intelligence to a novel congestion control approach for wireless sensor networks. ISABEL 2011: 78:1-78:7 - [c80]Mathys C. du Plessis, Andries P. Engelbrecht:
Self-adaptive competitive differential evolution for dynamic environments. SDE 2011: 41-48 - [c79]Andries P. Engelbrecht:
Scalability of a heterogeneous particle swarm optimizer. SWIS 2011: 1-8 - [c78]Barend Jacobus Leonard, Andries P. Engelbrecht, Andrich B. van Wyk:
Heterogeneous particle swarms in dynamic environments. SWIS 2011: 9-16 - [c77]Andrich B. van Wyk, Andries P. Engelbrecht:
Lambda-gamma learning with feedforward neural networks using particle swarm optimization. SWIS 2011: 52-59 - [c76]Gary Pampara, Andries P. Engelbrecht:
Binary artificial bee colony optimization. SWIS 2011: 170-177 - [c75]Ronald Klazar, Andries P. Engelbrecht:
Dynamic load balancing inspired by division of labour in ant colonies. SWIS 2011: 184-191 - 2010
- [c74]Andries P. Engelbrecht:
Heterogeneous Particle Swarm Optimization. ANTS Conference 2010: 191-202 - [c73]Isabella Schoeman, Andries P. Engelbrecht:
Effect of Particle Initialization on the Performance of Particle Swarm Niching Algorithms. ANTS Conference 2010: 560-561 - [c72]Jacomine Grobler, Andries P. Engelbrecht, Graham Kendall, Venkata S. S. Yadavalli:
Alternative hyper-heuristic strategies for multi-method global optimization. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c71]Leo Langenhoven, Willem S. van Heerden, Andries P. Engelbrecht:
Swarm Tetris: Applying particle swarm optimization to tetris. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c70]Andrich B. van Wyk, Andries P. Engelbrecht:
Overfitting by PSO trained feedforward neural networks. IEEE Congress on Evolutionary Computation 2010: 1-8 - 2009
- [c69]Mahamed G. H. Omran, Andries P. Engelbrecht:
Free Search Differential Evolution. IEEE Congress on Evolutionary Computation 2009: 110-117 - [c68]Anna S. Rakitianskaia, Andries P. Engelbrecht:
Training neural networks with PSO in dynamic environments. IEEE Congress on Evolutionary Computation 2009: 667-673 - [c67]Marius Riekert, Katherine M. Malan, Andries P. Engelbrecht:
Adaptive Genetic Programming for dynamic classification problems. IEEE Congress on Evolutionary Computation 2009: 674-681 - [c66]Jacomine Grobler, Andries P. Engelbrecht:
Hybridizing PSO and DE for improved vector evaluated multi-objective optimization. IEEE Congress on Evolutionary Computation 2009: 1255-1262 - [c65]Katherine M. Malan, Andries P. Engelbrecht:
Quantifying ruggedness of continuous landscapes using entropy. IEEE Congress on Evolutionary Computation 2009: 1440-1447 - [c64]Olusegun Olorunda, Andries P. Engelbrecht:
An analysis of heterogeneous cooperative algorithms. IEEE Congress on Evolutionary Computation 2009: 1562-1569 - [c63]Pavlos Antoniou, Andreas Pitsillides, Tim Blackwell, Andries P. Engelbrecht:
Employing the flocking behavior of birds for controlling congestion in autonomous decentralized networks. IEEE Congress on Evolutionary Computation 2009: 1753-1761 - [c62]Isabella Lona Schoeman, Andries P. Engelbrecht:
Scalability of the vector-based Particle Swarm Optimizer. IEEE Congress on Evolutionary Computation 2009: 1995-2001 - [c61]Willem S. van Heerden, Andries P. Engelbrecht:
HybridSOM: A generic rule extraction framework for self-organizing feature maps. CIDM 2009: 17-24 - [c60]Camiel Castillo, Geoff Nitschke, Andries P. Engelbrecht:
Niche Particle Swarm Optimization for Neural Network Ensembles. ECAL (2) 2009: 399-407 - [c59]Noor Khafifah Khalid, Zuwairie Ibrahim, Tri Basuki Kurniawan, Marzuki Khalid, Andries P. Engelbrecht:
Implementation of Binary Particle Swarm Optimization for DNA Sequence Design. IWANN (2) 2009: 450-457 - [c58]Pavlos Antoniou, Andreas Pitsillides, Andries P. Engelbrecht, Tim Blackwell, Loizos Michael:
Congestion Control in Wireless Sensor Networks Based on the Bird Flocking Behavior. IWSOS 2009: 220-225 - 2008
- [c57]Noor Khafifah Khalid, Tri Basuki Kurniawan, Zuwairie Ibrahim, Zulkifli Md. Yusof, Marzuki Khalid, Andries P. Engelbrecht:
A Model to Optimize DNA Sequences Based on Particle Swarm Optimization. Asia International Conference on Modelling and Simulation 2008: 534-539 - [c56]Mathys C. du Plessis, Andries P. Engelbrecht:
Improved differential evolution for dynamic optimization problems. IEEE Congress on Evolutionary Computation 2008: 229-234 - [c55]A. J. Graaff, Andries P. Engelbrecht:
Towards a self regulating local network neighbourhood artificial immune system for data clustering. IEEE Congress on Evolutionary Computation 2008: 633-640 - [c54]Katherine M. Malan, Andries P. Engelbrecht:
Algorithm comparisons and the significance of population size. IEEE Congress on Evolutionary Computation 2008: 914-920 - [c53]Anna S. Rakitianskaia, Andries P. Engelbrecht:
Cooperative charged particle swarm optimiser. IEEE Congress on Evolutionary Computation 2008: 933-939 - [c52]Olusegun Olorunda, Andries P. Engelbrecht:
Measuring exploration/exploitation in particle swarms using swarm diversity. IEEE Congress on Evolutionary Computation 2008: 1128-1134 - [c51]Jacomine Grobler, Andries P. Engelbrecht, Venkata S. S. Yadavalli:
Multi-objective DE and PSO strategies for production scheduling. IEEE Congress on Evolutionary Computation 2008: 1154-1161 - [c50]Mardé Greeff, Andries P. Engelbrecht:
Solving dynamic multi-objective problems with vector evaluated particle swarm optimisation. IEEE Congress on Evolutionary Computation 2008: 2917-2924 - [c49]Gary Pampara, Andries P. Engelbrecht, T. Cloete:
CIlib: A collaborative framework for Computational Intelligence algorithms - Part I. IJCNN 2008: 1750-1757 - [c48]T. Cloete, Andries P. Engelbrecht, Gary Pampara:
CIlib: A collaborative framework for Computational Intelligence algorithms - Part II. IJCNN 2008: 1764-1773 - [c47]Willem S. van Heerden, Andries P. Engelbrecht:
A comparison of map neuron labeling approaches for unsupervised self-organizing feature maps. IJCNN 2008: 2139-2146 - [c46]Salman A. Khan, Andries P. Engelbrecht:
A fuzzy ant colony optimization algorithm for topology design of distributed local area networks. SIS 2008: 1-7 - [c45]James Lane, Andries P. Engelbrecht, James E. Gain:
Particle swarm optimization with spatially meaningful neighbours. SIS 2008: 1-8 - 2007
- [c44]A. J. Graaff, Andries P. Engelbrecht:
A local network neighbourhood artificial immune system for data clustering. IEEE Congress on Evolutionary Computation 2007: 260-267 - [c43]Olusegun Olorunda, Andries P. Engelbrecht:
Differential evolution in high-dimensional search spaces. IEEE Congress on Evolutionary Computation 2007: 1934-1941 - [c42]Andries P. Engelbrecht, Gary Pampara:
Binary differential evolution strategies. IEEE Congress on Evolutionary Computation 2007: 1942-1947 - [c41]Mahamed G. H. Omran, Andries P. Engelbrecht:
Differential evolution for integer programming problems. IEEE Congress on Evolutionary Computation 2007: 2237-2242 - [c40]Andries P. Engelbrecht, L. N. H. van Loggerenberg:
Enhancing the NichePSO. IEEE Congress on Evolutionary Computation 2007: 2297-2302 - [c39]Mahamed G. H. Omran, Andries P. Engelbrecht, Ayed A. Salman:
Self-adaptive barebones differential evolution. IEEE Congress on Evolutionary Computation 2007: 2858-2865 - [c38]Willem H. Duminy, Andries P. Engelbrecht:
Tournament Particle Swarm Optimization. CIG 2007: 146-153 - [c37]Jacomine Grobler, Andries P. Engelbrecht, Johan W. Joubert, Schalk Kok:
A starting-time-based approach to production scheduling with Particle Swarm Optimization. CISched 2007: 121-128 - [c36]Xiaodong Li, Andries P. Engelbrecht:
Particle swarm optimization: an introduction and its recent developments. GECCO (Companion) 2007: 3391-3414 - [c35]Mahamed G. H. Omran, Andries P. Engelbrecht, Ayed A. Salman:
Differential Evolution Based Particle Swarm Optimization. SIS 2007: 112-119 - [c34]Mahamed G. H. Omran, Andries P. Engelbrecht, Ayed A. Salman:
Barebones Particle Swarm for Integer Programming Problems. SIS 2007: 170-175 - 2006
- [c33]Auralia I. Edwards, Andries P. Engelbrecht:
Comparing Particle Swarm Optimisation and Genetic Algorithms for Nonlinear Mapping. IEEE Congress on Evolutionary Computation 2006: 694-701 - [c32]Marais Neethling, Andries P. Engelbrecht:
Determining RNA Secondary Structure using Set-based Particle Swarm Optimization. IEEE Congress on Evolutionary Computation 2006: 1670-1677 - [c31]Gary Pampara, Andries P. Engelbrecht, Nelis Franken:
Binary Differential Evolution. IEEE Congress on Evolutionary Computation 2006: 1873-1879 - [c30]Johan Conradie, Andries P. Engelbrecht:
Training Bao Game-Playing Agents using Coevolutionary Particle Swarm Optimization. CIG 2006: 67-74 - [c29]Mahamed G. H. Omran, Andries P. Engelbrecht, Ayed A. Salman:
Using the Ring Neighborhood Topology with Self-adaptive Differential Evolution. ICNC (1) 2006: 976-979 - [c28]Isabella Schoeman, Andries P. Engelbrecht:
Niching for Dynamic Environments Using Particle Swarm Optimization. SEAL 2006: 134-141 - 2005
- [c27]Gary Pampara, Nelis Franken, Andries P. Engelbrecht:
Combining particle swarm optimisation with angle modulation to solve binary problems. Congress on Evolutionary Computation 2005: 89-96 - [c26]Nelis Franken, Andries P. Engelbrecht:
Investigating binary PSO parameter influence on the knights cover problem. Congress on Evolutionary Computation 2005: 282-289 - [c25]Auralia I. Edwards, Andries P. Engelbrecht, Nelis Franken:
Nonlinear mapping using particle swarm optimisation. Congress on Evolutionary Computation 2005: 306-313 - [c24]Mahamed G. H. Omran, Andries P. Engelbrecht, Ayed A. Salman:
Differential evolution methods for unsupervised image classification. Congress on Evolutionary Computation 2005: 966-973 - [c23]Evangelos Papacostantis, Andries P. Engelbrecht, Nelis Franken:
Coevolving Probabilistic Game Playing Agents using Particle Swarm Optimization Algorithm. CIG 2005 - [c22]Mahamed G. H. Omran, Ayed A. Salman, Andries P. Engelbrecht:
Self-adaptive Differential Evolution. CIS (1) 2005: 192-199 - [c21]Edwin S. Peer, Andries P. Engelbrecht, Gary Pampara, B. S. Masiye:
CiClops: computational intelligence collaborative laboratory of pantological software. SIS 2005: 130-137 - [c20]Andries P. Engelbrecht, B. S. Masiye, G. Pampard:
Niching ability of basic particle swarm optimization algorithms. SIS 2005: 397-400 - 2004
- [c19]Nelis Franken, Andries P. Engelbrecht:
PSO approaches to coevolve IPD strategies. IEEE Congress on Evolutionary Computation 2004: 356-363 - 2003
- [c18]D. W. van der Merwe, Andries P. Engelbrecht:
Data clustering using particle swarm optimization. IEEE Congress on Evolutionary Computation 2003: 215-220 - [c17]Ulrich Paquet, Andries P. Engelbrecht:
A new particle swarm optimiser for linearly constrained optimisation. IEEE Congress on Evolutionary Computation 2003: 227-233 - [c16]Nelis Franken, Andries P. Engelbrecht:
Comparing PSO structures to learn the game of checkers from zero knowledge. IEEE Congress on Evolutionary Computation 2003: 234-241 - [c15]Edwin S. Peer, Andries P. Engelbrecht, Frans van den Bergh:
CIRG@UP OptiBench: a statistically sound framework for benchmarking optimisation algorithms. IEEE Congress on Evolutionary Computation 2003: 2386-2392 - [c14]R. Brits, Andries P. Engelbrecht, Frans van den Bergh:
Scalability of niche PSO. SIS 2003: 228-234 - [c13]Edwin S. Peer, Frans van den Bergh, Andries P. Engelbrecht:
Using neighbourhoods with the guaranteed convergence PSO. SIS 2003: 235-242 - 2002
- [c12]Mahamed G. H. Omran, Andries P. Engelbrecht, Ayed A. Salman:
Image Classification using Particle Swarm Optimization. SEAL 2002: 347-365 - 2001
- [c11]Andries P. Engelbrecht:
Selective Learning for Multilayer Feedforward Neural Networks. IWANN (1) 2001: 386-393 - 2000
- [c10]S. E. Rouwhorst, Andries P. Engelbrecht:
Searching the forest: using decision trees as building blocks for evolutionary search in classification databases. CEC 2000: 633-638 - [c9]Adiel Ismail, Andries P. Engelbrecht:
Global Optimization Algorithms for Training Product Unit Neural Networks. IJCNN (1) 2000: 132-137 - 1999
- [c8]E. Basson, Andries P. Engelbrecht:
Approximation of a function and its derivatives in feedforward neural networks. IJCNN 1999: 419-421 - [c7]Andries P. Engelbrecht, Ian Cloete:
Incremental learning using sensitivity analysis. IJCNN 1999: 1350-1355 - [c6]Andries P. Engelbrecht, L. Fletcher, Ian Cloete:
Variance analysis of sensitivity information for pruning multilayer feedforward neural networks. IJCNN 1999: 1829-1833 - [c5]Andries P. Engelbrecht, Herna L. Viktor:
Rule Improvement Through Decision Boundary Detection Using Sensitivity Analysis. IWANN (2) 1999: 78-84 - 1996
- [c4]Andries P. Engelbrecht, Ian Cloete:
A sensitivity analysis algorithm for pruning feedforward neural networks. ICNN 1996: 1274-1278 - 1995
- [c3]Herna L. Viktor, Andries P. Engelbrecht, Ian Cloete:
Reduction of symbolic rules from artificial neural networks using sensitivity analysis. ICNN 1995: 1788-1793 - [c2]Andries P. Engelbrecht, Ian Cloete, Jaco Geldenhuys, Jacek M. Zurada:
Automatic Scaling using Gamma Learning for Feedforward Neural Networks. IWANN 1995: 374-381 - [c1]Andries P. Engelbrecht, Ian Cloete, Jacek M. Zurada:
Determining the Significance of Input Parameters using Sensitivity Analysis. IWANN 1995: 382-388
Parts in Books or Collections
- 2013
- [p4]Mathys C. du Plessis, Andries P. Engelbrecht:
Self-Adaptive Differential Evolution for Dynamic Environments with Fluctuating Numbers of Optima. Metaheuristics for Dynamic Optimization 2013: 117-145 - [p3]Mardé Helbig, Andries P. Engelbrecht:
Dynamic Multi-Objective Optimization Using PSO. Metaheuristics for Dynamic Optimization 2013: 147-188 - 2010
- [p2]Mardé Greeff, Andries P. Engelbrecht:
Dynamic Multi-objective Optimisation Using PSO. Multi-Objective Swarm Intelligent System 2010: 105-123 - 2006
- [p1]Mahamed G. H. Omran, Andries P. Engelbrecht, Ayed A. Salman:
Particle Swarm Optimization for Pattern Recognition and Image Processing. Swarm Intelligence in Data Mining 2006: 125-151
Editorship
- 2022
- [e8]Marco Dorigo, Heiko Hamann, Manuel López-Ibáñez, José García-Nieto, Andries P. Engelbrecht, Carlo Pinciroli, Volker Strobel, Christian Leonardo Camacho-Villalón:
Swarm Intelligence - 13th International Conference, ANTS 2022, Málaga, Spain, November 2-4, 2022, Proceedings. Lecture Notes in Computer Science 13491, Springer 2022, ISBN 978-3-031-20175-2 [contents] - 2016
- [e7]Nelishia Pillay, Andries P. Engelbrecht, Ajith Abraham, Mathys C. du Plessis, Václav Snásel, Azah Kamilah Muda:
Advances in Nature and Biologically Inspired Computing - Proceedings of the 7th World Congress on Nature and Biologically Inspired Computing (NaBIC 2015) in Pietermaritzburg, South Africa, held December 01-03, 2015. Advances in Intelligent Systems and Computing 419, Springer 2016, ISBN 978-3-319-27399-0 [contents] - 2015
- [e6]Ying Tan, Yuhui Shi, Fernando Buarque de Lima Neto, Alexander F. Gelbukh, Swagatam Das, Andries P. Engelbrecht:
Advances in Swarm and Computational Intelligence - 6th International Conference, ICSI 2015, held in conjunction with the Second BRICS Congress, CCI 2015, Beijing, China, June 25-28, 2015, Proceedings, Part I. Lecture Notes in Computer Science 9140, Springer 2015, ISBN 978-3-319-20465-9 [contents] - [e5]Ying Tan, Yuhui Shi, Fernando Buarque de Lima Neto, Alexander F. Gelbukh, Swagatam Das, Andries P. Engelbrecht:
Advances in Swarm and Computational Intelligence - 6th International Conference, ICSI 2015, held in conjunction with the Second BRICS Congress, CCI 2015, Beijing, China, June 25-28, 2015, Proceedings, Part II. Lecture Notes in Computer Science 9141, Springer 2015, ISBN 978-3-319-20471-0 [contents] - [e4]Ying Tan, Yuhui Shi, Fernando Buarque de Lima Neto, Alexander F. Gelbukh, Swagatam Das, Andries P. Engelbrecht:
Advances in Swarm and Computational Intelligence - 6th International Conference, ICSI 2015, held in conjunction with the Second BRICS Congress, CCI 2015, Beijing, China, June 25-28, 2015, Proceedings, Part III. Lecture Notes in Computer Science 9142, Springer 2015, ISBN 978-3-319-20468-0 [contents] - 2012
- [e3]Marco Dorigo, Mauro Birattari, Christian Blum, Anders Lyhne Christensen, Andries P. Engelbrecht, Roderich Groß, Thomas Stützle:
Swarm Intelligence - 8th International Conference, ANTS 2012, Brussels, Belgium, September 12-14, 2012. Proceedings. Lecture Notes in Computer Science 7461, Springer 2012, ISBN 978-3-642-32649-3 [contents] - 2010
- [e2]Marco Dorigo, Mauro Birattari, Gianni A. Di Caro, René Doursat, Andries P. Engelbrecht, Dario Floreano, Luca Maria Gambardella, Roderich Groß, Erol Sahin, Hiroki Sayama, Thomas Stützle:
Swarm Intelligence - 7th International Conference, ANTS 2010, Brussels, Belgium, September 8-10, 2010. Proceedings. Lecture Notes in Computer Science 6234, Springer 2010, ISBN 978-3-642-15460-7 [contents] - 2009
- [e1]Ajith Abraham, Aboul Ella Hassanien, Patrick Siarry, Andries P. Engelbrecht:
Foundations of Computational Intelligence - Volume 3: Global Optimization. Studies in Computational Intelligence 203, Springer 2009, ISBN 978-3-642-01084-2 [contents]
Informal and Other Publications
- 2023
- [i8]Arné Schreuder, Anna S. Bosman, Andries P. Engelbrecht, Christopher W. Cleghorn:
Training Feedforward Neural Networks with Bayesian Hyper-Heuristics. CoRR abs/2303.16912 (2023) - [i7]Ana Nikolikj, Gjorgjina Cenikj, Gordana Ispirova, Diederick Vermetten, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
Assessing the Generalizability of a Performance Predictive Model. CoRR abs/2306.00040 (2023) - [i6]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Empirical Loss Landscape Analysis of Neural Network Activation Functions. CoRR abs/2306.16090 (2023) - 2022
- [i5]Gjorgjina Cenikj, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
SELECTOR: Selecting a Representative Benchmark Suite for Reproducible Statistical Comparison. CoRR abs/2204.11527 (2022) - 2020
- [i4]Andreas Kamilaris, Andries P. Engelbrecht, Andreas Pitsillides, Francesc X. Prenafeta-Boldu:
Transfer of Manure from Livestock Farms to Crop Fields as Fertilizer using an Ant Inspired Approach. CoRR abs/2006.04573 (2020) - [i3]Andreas Kamilaris, Andries P. Engelbrecht, Andreas Pitsillides, Francesc X. Prenafeta-Boldu:
Transfer of Manure as Fertilizer from Livestock Farms to Crop Fields: The Case of Catalonia. CoRR abs/2006.09122 (2020) - 2019
- [i2]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Visualising Basins of Attraction for the Cross-Entropy and the Squared Error Neural Network Loss Functions. CoRR abs/1901.02302 (2019) - [i1]Anna Sergeevna Bosman, Andries P. Engelbrecht, Mardé Helbig:
Loss Surface Modality of Feed-Forward Neural Network Architectures. CoRR abs/1905.10268 (2019)
Coauthor Index
Christopher W. Cleghorn
aka: Christopher Wesley Cleghorn
aka: Christopher Wesley Cleghorn
Mardé Helbig
aka: Mardé Greeff
aka: Mardé Greeff
Mahamed Ghasib Hussein Omran
aka: Mahamed G. H. Omran
aka: Mahamed G. H. Omran
Gary Pampara
aka: Gary Pamparà
aka: Gary Pamparà
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