Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/7884
Title: An evolving neural network approach in unit commitment solution
Authors: Wong, M
Chung, T
Wong, Y
Keywords: Genetic algorithm
Unit commitment problem
Neural network
Issue Date: 2000
Publisher: Elsevier Science Bv
Source: Microprocessors and microsystems, 2000, v. 24, no. 5, p. 251-262 How to cite?
Journal: Microprocessors and Microsystems 
Abstract: In this paper, the Genetic Algorithm (GA) is used to evolve the weight and the interconnection of the neural network to solve the Unit Commitment problem. We will emphasize on the determination of the appropriate GA parameters to evolve the neural network, i.e. the population size and probabilities of crossover and mutation, and the method used for selection amongst generations such as Tournament selection, Roulette Wheel selection and Ranking selection. Performance comparisons are conducted to analyze the learning curve of different parameters, to find out which has a dominant influence on the effectiveness of the algorithm.
URI: http://hdl.handle.net/10397/7884
ISSN: 0141-9331
DOI: 10.1016/S0141-9331(00)00076-4
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