Genetic-based Kohonen's neural networks for power system static security assessment

Shyh Jier Huang, Chuan Chang Hung

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper proposes Kohonen's self-organizing neural networks embedded with genetic algorithms. The genetic algorithms are applied to decide initial weights in the Kohonen's classifiers. These initialized neural networks are then trained with training data and validated through the testing data. The proposed hybrid system has been tested on the power system static security assessment problems. The satisfactory results from both a standard test system and utility data reveal their potentials for applications.

Original languageEnglish
Pages791-796
Number of pages6
Publication statusPublished - 1995
EventProceedings of the 1995 Artificial Neural Networks in Engineering, ANNIE'95 - St.Louis, MO, USA
Duration: 1995 Nov 121995 Nov 15

Other

OtherProceedings of the 1995 Artificial Neural Networks in Engineering, ANNIE'95
CitySt.Louis, MO, USA
Period95-11-1295-11-15

All Science Journal Classification (ASJC) codes

  • Software

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