Items where Author is "Khosravi, A."

Hassan, S. and Khanesar, M.A. and Jaafar, J. and Khosravi, A. (2018) Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm. Neural Computing and Applications, 29 (4). pp. 1001-1014.

Hassan, S. and Khanesar, M.A. and Jaafar, J. and Khosravi, A. (2017) Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS. Applied Soft Computing Journal, 51. pp. 130-144.

Hassan, S. and Khanesar, M.A. and Jaafar, J. and Khosravi, A. (2017) A multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems. 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. pp. 155-160.

Hassan, S. and Jaafar, J. and Khanesar, M.A. and Khosravi, A. (2016) Artificial bee colony optimization of interval type-2 fuzzy extreme learning system for chaotic data. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. (2016) The impact of FOU size and number of MFs on the prediction performance of Interval Type-2 Fuzzy Logic Systems. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. (2016) The impact of FOU size and number of MFs on the prediction performance of Interval Type-2 Fuzzy Logic Systems. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. and Khanesar, M.A. (2016) A systematic design of interval type-2 fuzzy logic system using extreme learning machine for electricity load demand forecasting. International Journal of Electrical Power and Energy Systems, 82. pp. 1-10.

Hassan, S. and Khosravi, A. and Jaafar, J. (2015) Examining performance of aggregation algorithms for neural network-based electricity demand forecasting. International Journal of Electrical Power and Energy Systems, 64. pp. 1098-1105.

Hassan, S. and Khosravi, A. and Jaafar, J. (2015) Training of interval type-2 fuzzy logic system using extreme learning machine for load forecasting. In: UNSPECIFIED.

Raza, M.Q. and Khosravi, A. (2015) A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings. Renewable and Sustainable Energy Reviews, 50. pp. 1352-1372. ISSN 13640321

Hassan, S. and Khosravi, A. and Jaafar, J. and Raza, M.Q. (2014) Electricity load and price forecasting with influential factors in a deregulated power industry. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. (2013) Bayesian model averaging of load demand forecasts from neural network models. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. (2013) Bayesian model averaging of load demand forecasts from neural network models. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. (2013) Bayesian model averaging of load demand forecasts from neural network models. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. (2013) Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. (2013) Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. (2013) Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. (2013) Variance-covariance based weighing for neural network ensembles. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. (2013) Variance-covariance based weighing for neural network ensembles. In: UNSPECIFIED.

Hassan, S. and Khosravi, A. and Jaafar, J. (2013) Variance-covariance based weighing for neural network ensembles. In: UNSPECIFIED.