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 language | English |
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Title of host publication | Proceedings of the International Conference on Intelligent Systems Applications to Power Systems, ISAP |
Publisher | IEEE |
Pages | 44-49 |
Number of pages | 6 |
Publication status | Published - 1996 |
Event | Proceedings of the 1996 International Conference on Intelligent Systems Applications to Power Systems - Orlando, FL, USA Duration: 1996 Jan 28 → 1996 Feb 2 |
Other
Other | Proceedings of the 1996 International Conference on Intelligent Systems Applications to Power Systems |
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City | Orlando, FL, USA |
Period | 96-01-28 → 96-02-02 |
All Science Journal Classification (ASJC) codes
- General Computer Science
- General Energy
- General Engineering