Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75283
Title: A hybrid genetic algorithm/particle swarm approach for evaluation of power flow in electric network
Authors: Ting, TO 
Wong, KP 
Chung, CY 
Issue Date: 2006
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2006, v. 3930 LNAI, p. 908-917 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: This paper presents an investigation of possible hybrid genetic algorithm / particle swarm optimization approaches to evaluate the flow of electric power in power transmission network. The possible schemes are presented and their performances are illustrated by applying them to the power flow problem of the Klos Kerner 11-busbar system. The performance of the hybrid algorithm in terms of reliability is further improved by applying the optimal values for both inertia weight and mutation probability which are found through parameter sensitivity analyses.
Description: 4th International Conference on Machine Learning and Cybernetics, ICMLC 2005, Guangzhou, 18-21 August 2005
URI: http://hdl.handle.net/10397/75283
ISBN: 3540335846
9783540335849
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/11739685_95
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