Abstract
A new approach of using genetic algorithms to improve the learning characteristics of Kohonen's neural networks is proposed in this paper. In the proposed scheme, genetic algorithms are applied to decide initial weights in the Kohonen's classifiers. The competitive learning is then applied to train neural networks. The proposed method was tested on the power system static security assessment and travelling salesperson problems. The results were very promising to applications.
Original language | English |
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Pages | 708-712 |
Number of pages | 5 |
Publication status | Published - 1995 Dec 1 |
Event | Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust Duration: 1995 Nov 27 → 1995 Dec 1 |
Other
Other | Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) |
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City | Perth, Aust |
Period | 95-11-27 → 95-12-01 |
All Science Journal Classification (ASJC) codes
- Software