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Jafreezal Jaafar
- > Home > Persons > Jafreezal Jaafar
Publications
- 2018
- [j10]Saima Hassan, Mojtaba Ahmadieh Khanesar, Jafreezal Jaafar, Abbas Khosravi:
Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm. Neural Comput. Appl. 29(4): 1001-1014 (2018) - 2017
- [j8]Saima Hassan, Mojtaba Ahmadieh Khanesar, Jafreezal Jaafar, Abbas Khosravi:
Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS. Appl. Soft Comput. 51: 130-144 (2017) - 2016
- [j5]Saima Hassan, Mojtaba Ahmadieh Khanesar, Erdal Kayacan, Jafreezal Jaafar, Abbas Khosravi:
Optimal design of adaptive type-2 neuro-fuzzy systems: A review. Appl. Soft Comput. 44: 134-143 (2016) - [c22]Saima Hassan, Mojtaba Ahmadieh Khanesar, Jafreezal Jaafar, Abbas Khosravi:
A multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems. SMC 2016: 155-160 - 2015
- [c19]Saima Hassan, Abbas Khosravi, Jafreezal Jaafar, Mojtaba Ahmadieh Khanesar:
Hybrid Model for the Training of Interval Type-2 Fuzzy Logic System. ICONIP (1) 2015: 644-653 - [c18]Saima Hassan, Abbas Khosravi, Jafreezal Jaafar:
Training of interval type-2 fuzzy logic system using extreme learning machine for load forecasting. IMCOM 2015: 87:1-87:5 - 2014
- [c14]Saima Hassan, Abbas Khosravi, Jafreezal Jaafar, Muhammad Qamar Raza:
Electricity load and price forecasting with influential factors in a deregulated power industry. SoSE 2014: 79-84 - 2013
- [c11]Saima Hassan, Abbas Khosravi, Jafreezal Jaafar:
Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting. IJCNN 2013: 1-6 - [c9]Saima Hassan, Abbas Khosravi, Jafreezal Jaafar:
Bayesian Model Averaging of Load Demand Forecasts from Neural Network Models. SMC 2013: 3192-3197 - [c8]Saima Hassan, Abbas Khosravi, Jafreezal Jaafar:
Variance-Covariance Based Weighing for Neural Network Ensembles. SMC 2013: 3214-3219 - 2012
- [c7]Saima Hassan, Abbas Khosravi, Jafreezal Jaafar, Samir B. Belhaouari:
Load Forecasting Accuracy through Combination of Trimmed Forecasts. ICONIP (1) 2012: 152-159
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