대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)
- 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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- Pages.2075-2076
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- 2006
유전자 알고리즘을 이용한 신경 회로망 성능향상에 관한 연구
A study on Performance Improvement of Neural Networks Using Genetic algorithms
- Lim, Jung-Eun (Kyungpook Nat. Univ. Graduation School) ;
- Kim, Hae-Jin (Kyungpook Nat. Univ. Graduation School) ;
- Chang, Byung-Chan (Kyungpook Nat. Univ. Graduation School) ;
- Seo, Bo-Hyeok (Kyungpook Nat. Univ.)
- 발행 : 2006.07.12
초록
In this paper, we propose a new architecture of Genetic Algorithms(GAs)-based Backpropagation(BP). The conventional BP does not guarantee that the BP generated through learning has the optimal network architecture. But the proposed GA-based BP enable the architecture to be a structurally more optimized network, and to be much more flexible and preferable neural network than the conventional BP. The experimental results in BP neural network optimization show that this algorithm can effectively avoid BP network converging to local optimum. It is found by comparison that the improved genetic algorithm can almost avoid the trap of local optimum and effectively improve the convergent speed.
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