Development of genetic algorithm embedded Kohonen neural network for dynamic security assessment

M. A. El-Sharkawi, Shyh-Jier Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

A Kohonen self-organizing neural network embedded with genetic algorithm is proposed in this paper. The genetic algorithm is embedded to initiate the Kohonen classifiers. By the proposed approach, the neural network learning performance and accuracy are greatly enhanced. In addition, the genetic algorithm can successfully avoid the neural network from being trapped in a local minimum. The proposed method is developed and tested on an electric utility system to access its dynamic security.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Intelligent Systems Applications to Power Systems, ISAP
PublisherIEEE
Pages44-49
Number of pages6
Publication statusPublished - 1996
EventProceedings of the 1996 International Conference on Intelligent Systems Applications to Power Systems - Orlando, FL, USA
Duration: 1996 Jan 281996 Feb 2

Other

OtherProceedings of the 1996 International Conference on Intelligent Systems Applications to Power Systems
CityOrlando, FL, USA
Period96-01-2896-02-02

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Energy(all)
  • Engineering(all)

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