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ORCIDEd Keedwell
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- affiliation: University of Exeter, UK
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2020 – today
- 2020
[c45]Clodomir J. Santana Jr., Edward Keedwell, Ronaldo Menezes:
An approach to assess swarm intelligence algorithms based on complex networks. GECCO 2020: 31-39- [c44]Matthew Barrie Johns, Herman A. Mahmoud, Edward C. Keedwell, Dragan A. Savic:
Adaptive augmented evolutionary intelligence for the design of water distribution networks. GECCO 2020: 1116-1124 - [c43]Nicholas D. F. Ross
, Ed Keedwell, Dragan A. Savic:
Human-Derived Heuristic Enhancement of an Evolutionary Algorithm for the 2D Bin-Packing Problem. PPSN (2) 2020: 413-427
2010 – 2019
- 2019
- [j17]William B. Yates, Edward C. Keedwell:
An analysis of heuristic subsequences for offline hyper-heuristic learning. J. Heuristics 25(3): 399-430 (2019) - [c42]Ethan Bunce, Edward Keedwell:
Optimisation of a Checkers Player Using Neural and Metaheuristic Approaches. EA 2019: 53-67 - [c41]William B. Yates, Edward C. Keedwell:
Analysing heuristic subsequences for offline hyper-heuristic learning. GECCO (Companion) 2019: 37-38 - [c40]Diane P. Fraser, Edward Keedwell, Stephen L. Michell, Ray Sheridan:
EMOCS: evolutionary multi-objective optimisation for clinical scorecard generation. GECCO 2019: 1174-1182 - [c39]Matthew Barrie Johns, Herman A. Mahmoud, David J. Walker, Nicholas D. F. Ross, Edward C. Keedwell, Dragan A. Savic:
Augmented evolutionary intelligence: combining human and evolutionary design for water distribution network optimisation. GECCO 2019: 1214-1222 - [c38]Nicholas D. F. Ross, Matthew Barrie Johns, Edward C. Keedwell, Dragan A. Savic:
Human-evolutionary problem solving through gamification of a bin-packing problem. GECCO (Companion) 2019: 1465-1473 - 2018
- [c37]Hojjat Rakhshani, Lhassane Idoumghar, Julien Lepagnot, Mathieu Brévilliers, Edward Keedwell:
Automatic hyperparameter selection in Autodock. BIBM 2018: 734-738 - [c36]Dennis G. Wilson, Silvio Rodrigues, Carlos Segura, Ilya Loshchilov, Frank Hutter, Guillermo López Buenfil, Ahmed Kheiri, Ed Keedwell, Mario Ocampo-Pineda, Ender Özcan, Sergio Iwan Valdez Pea, Brian Goldman, Salvador Botello Rionda, Arturo Hernández Aguirre, Kalyan Veeramachaneni, Sylvain Cussat-Blanc:
Summary of evolutionary computation for wind farm layout optimization. GECCO (Companion) 2018: 31-32 - [c35]Ahamed Fayeez Tuani, Ed Keedwell, Matthew Collett:
Investigating Behavioural Diversity via Gaussian Heterogeneous Ant Colony Optimization for Combinatorial Optimization Problems. ICAAI 2018: 46-50 - [c34]Edward Keedwell, Mathieu Brévilliers, Lhassane Idoumghar, Julien Lepagnot, Hojjat Rakhshani:
A Novel Population Initialization Method Based on Support Vector Machine. SMC 2018: 751-756 - [i1]Hojjat Rakhshani, Lhassane Idoumghar, Julien Lepagnot, Mathieu Brévilliers, Edward Keedwell:
Automatic hyperparameter selection in Autodock. CoRR abs/1812.02618 (2018) - 2017
- [j16]Ahmed Kheiri, Ed Keedwell:
A Hidden Markov Model Approach to the Problem of Heuristic Selection in Hyper-Heuristics with a Case Study in High School Timetabling Problems. Evol. Comput. 25(3): 473-501 (2017) - [c33]Ahamed Fayeez Tuani, Edward Keedwell, Matthew Collett:
H-ACO: A Heterogeneous Ant Colony Optimisation Approach with Application to the Travelling Salesman Problem. Artificial Evolution 2017: 144-161 - [c32]William B. Yates, Edward C. Keedwell:
Offline Learning for Selection Hyper-heuristics with Elman Networks. Artificial Evolution 2017: 217-230 - [c31]William B. Yates, Edward C. Keedwell:
Clustering of hyper-heuristic selections using the Smith-Waterman algorithm for offline learning. GECCO (Companion) 2017: 119-120 - 2016
- [j15]Michele Guidolin, Albert S. Chen, Bidur Ghimire, Edward Keedwell, Slobodan Djordjevic, Dragan A. Savic:
A weighted cellular automata 2D inundation model for rapid flood analysis. Environ. Model. Softw. 84: 378-394 (2016) - [c30]David J. Walker, Ed Keedwell:
Multi-objective Optimisation with a Sequence-based Selection Hyper-heuristic. GECCO (Companion) 2016: 81-82 - [c29]David J. Walker, Ed Keedwell:
Towards Many-Objective Optimisation with Hyper-heuristics: Identifying Good Heuristics with Indicators. PPSN 2016: 493-502 - 2015
- [j14]Emmanuel Sapin, Edward Keedwell, Timothy M. Frayling:
An Ant Colony Optimization and Tabu List Approach to the Detection of Gene-Gene Interactions in Genome-Wide Association Studies [Research Frontier]. IEEE Comput. Intell. Mag. 10(4): 54-65 (2015) - [j13]Kent McClymont, Ed Keedwell, Dragan A. Savic:
An analysis of the interface between evolutionary algorithm operators and problem features for water resources problems. A case study in water distribution network design. Environ. Model. Softw. 69: 414-424 (2015) - [j12]Jonathan Mwaura, Ed Keedwell:
Evolving robot sub-behaviour modules using Gene Expression Programming. Genet. Program. Evolvable Mach. 16(2): 95-131 (2015) - [j11]Michael John Gibson, Edward Keedwell, Dragan A. Savic:
An investigation of the efficient implementation of cellular automata on multi-core CPU and GPU hardware. J. Parallel Distributed Comput. 77: 11-25 (2015) - [c28]Ahmed Kheiri, Ed Keedwell:
A Sequence-based Selection Hyper-heuristic Utilising a Hidden Markov Model. GECCO 2015: 417-424 - [c27]Edward Keedwell, Matthew Barrie Johns, Dragan A. Savic:
Spatial and Temporal Visualisation of Evolutionary Algorithm Decisions in Water Distribution Network Optimisation. GECCO (Companion) 2015: 941-948 - [c26]Jonathan Mwaura, Ed Keedwell:
Evolving Robotic Neuro-Controllers Using Gene Expression Programming. SSCI 2015: 1063-1072 - 2014
- [j10]Joe Townsend, Ed Keedwell, Antony Galton:
Artificial Development of Biologically Plausible Neural-Symbolic Networks. Cogn. Comput. 6(1): 18-34 (2014) - [j9]Holger R. Maier, Zoran Kapelan, Joseph R. Kasprzyk, Joshua B. Kollat, L. Shawn Matott, Maria C. Cunha, Graeme C. Dandy, Matthew S. Gibbs, Ed Keedwell, Angela Marchi, Avi Ostfeld, Dragan A. Savic, D. P. Solomatine, Jasper A. Vrugt, Aaron C. Zecchin, Barbara S. Minsker, E. J. Barbour, George Kuczera, F. Pasha, Andrea Castelletti, Matteo Giuliani, Patrick M. Reed:
Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions. Environ. Model. Softw. 62: 271-299 (2014) - [j8]Emmanuel Sapin, Ed Keedwell:
A Subset-Based Ant Colony Optimisation with Tournament Path Selection for High-Dimensional Problems. Trans. Comput. Collect. Intell. 17: 232-247 (2014) - [c25]Ed Keedwell:
An analysis of the area under the ROC curve and its use as a metric for comparing clinical scorecards. BIBM 2014: 24-29 - [c24]Emmanuel Sapin, Ed Keedwell, Timothy M. Frayling:
Ant colony optimisation of decision trees for the detection of gene-gene interactions. BIBM 2014: 57-61 - [c23]Jonathan Mwaura, Ed Keedwell:
On using Gene Expression Programming to evolve multiple output robot controllers. ICES 2014: 173-180 - [c22]Ajit Narayanan, Edward Keedwell:
An evolutionary computational approach to phase and synchronization in biological circuits. ICNC 2014: 419-424 - 2013
- [j7]Ed Keedwell, Ajit Narayanan:
Gene expression rule discovery and multi-objective ROC analysis using a neural-genetic hybrid. Int. J. Data Min. Bioinform. 7(4): 376-396 (2013) - [c21]Joe Townsend, Ed Keedwell, Antony Galton:
Artificial development of connections in SHRUTI networks using a multi objective genetic algorithm. GECCO (Companion) 2013: 111-112 - [c20]Mike J. Gibson, Ed Keedwell, Dragan A. Savic:
Understanding the efficient parallelisation of cellular automata on CPU and GPGPU hardware. GECCO (Companion) 2013: 171-172 - [c19]Emmanuel Sapin, Ed Keedwell, Timothy M. Frayling:
Subset-based ant colony optimisation for the discovery of gene-gene interactions in genome wide association studies. GECCO 2013: 295-302 - [c18]Matthew Barrie Johns, Edward Keedwell, Dragan A. Savic:
Pipe smoothing genetic algorithm for least cost water distribution network design. GECCO 2013: 1309-1316 - [c17]Emmanuel Sapin, Ed Keedwell, Timothy M. Frayling:
Ant Colony Optimisation for Exploring Logical Gene-Gene Associations in Genome Wide Association Studies. IWBBIO 2013: 449-456 - 2012
- [j6]Kent McClymont, Ed Keedwell:
Deductive Sort and Climbing Sort: New Methods for Non-Dominated Sorting. Evol. Comput. 20(1): 1-26 (2012) - [c16]Ed Keedwell, Mark Morley, Darren Croft:
Continuous Trait-Based Particle Swarm Optimisation (CTB-PSO). ANTS 2012: 342-343 - [c15]Emmanuel Sapin, Ed Keedwell:
T-ACO Tournament Ant Colony Optimisation for High-dimensional Problems. IJCCI 2012: 81-86 - 2011
- [j5]Jacqueline Christmas, Edward Keedwell, Timothy M. Frayling, John R. B. Perry:
Ant colony optimisation to identify genetic variant association with type 2 diabetes. Inf. Sci. 181(9): 1609-1622 (2011) - [c14]Kent McClymont, Ed Keedwell:
Benchmark multi-objective optimisation test problems with mixed encodings. IEEE Congress on Evolutionary Computation 2011: 2131-2138 - [c13]Kent McClymont, Edward Keedwell:
Markov chain hyper-heuristic (MCHH): an online selective hyper-heuristic for multi-objective continuous problems. GECCO 2011: 2003-2010 - [c12]Jonathan Mwaura, Ed Keedwell:
Evolving Modularity in Robot Behaviour Using Gene Expression Programming. TAROS 2011: 392-393 - 2010
- [c11]Ed Keedwell, Ajit Narayanan:
Gene expression rule discovery with a multi-objective neural-genetic hybrid. BIBM 2010: 649-656 - [c10]Kent McClymont, Ed Keedwell:
Optimising multi-modal polynomial mutation operators for multi-objective problem classes. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c9]Jonathan Mwaura, Ed Keedwell:
Evolution of robotic behaviours using Gene Expression Programming. IEEE Congress on Evolutionary Computation 2010: 1-8
2000 – 2009
- 2007
- [c8]Ed Keedwell, Ajit Narayanan:
Gene finding and rule discovery with a multi-objective neural-genetic hybrid. GECCO 2007: 428 - 2006
- [c7]Yufeng Guo, Ed Keedwell, Godfrey A. Walters, Soon-Thiam Khu:
Hybridizing Cellular Automata Principles and NSGAII for Multi-objective Design of Urban Water Networks. EMO 2006: 546-559 - 2005
- [j4]Edward Keedwell, Soon-Thiam Khu:
A hybrid genetic algorithm for the design of water distribution networks. Eng. Appl. Artif. Intell. 18(4): 461-472 (2005) - [j3]Ed Keedwell, Ajit Narayanan:
Discovering Gene Networks with a Neural-Genetic Hybrid. IEEE ACM Trans. Comput. Biol. Bioinform. 2(3): 231-242 (2005) - [c6]Thorhildur Juliusdottir, David Corne, Ed Keedwell, Ajit Narayanan:
Two-Phase EA/k-NN for Feature Selection and Classification in Cancer Microarray Datasets. CIBCB 2005: 1-8 - [c5]A. Krishna, Ajit Narayanan, Ed Keedwell:
Neural Networks and Temporal Gene Expression Data. EvoWorkshops 2005: 64-73 - 2004
- [j2]Ajit Narayanan, Ed Keedwell, Jonas Gamalielsson, S. Tatineni:
Single-layer artificial neural networks for gene expression analysis. Neurocomputing 61: 217-240 (2004) - [c4]Ajit Narayanan, Evangelia Nana, Ed Keedwell:
Analyzing gene expression data for childhood medulloblastoma survival with artificial neural networks. CIBCB 2004: 9-16 - [c3]Ed Keedwell, Soon-Thiam Khu:
Hybrid Genetic Algorithms for Multi-Objective Optimisation of Water Distribution Networks. GECCO (2) 2004: 1042-1053 - 2003
- [b1]Edward Keedwell:
Knowledge discovery from gene expression data using neural-genetic models : a comparative study of four European countries with special attention to the education of these children. University of Exeter, Devon, UK, 2003 - [c2]Ed Keedwell, Ajit Narayanan:
Genetic Algorithms for Gene Expression Analysis. EvoWorkshops 2003: 76-86 - 2000
- [j1]Ed Keedwell, Ajit Narayanan, Dragan A. Savic:
Creating rules from trained networks using genetic algorithms. Int. J. Comput. Syst. Signals 1(1): 30-42 (2000) - [c1]Ed Keedwell, Florian Bessler, Ajit Narayanan, Dragan A. Savic:
From data mining to rule refining A new tool for post data mining rule optimisation. ICTAI 2000: 82-85
Coauthor Index
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