대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)
- 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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- Pages.337-339
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- 2004
진화론적 최적 퍼지다항식 신경회로망 모델 및 소프트웨어 공정으로의 응용
Genetically Optimized Fuzzy Polynomial Neural Networks Model and Its Application to Software Process
- 발행 : 2004.11.12
초록
In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs). Proceeding the layer, this model creates the optimal network architecture through the selection and the elimination of nodes by itself. So, there is characteristic of flexibility. We use a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. GAs is applied to improve the performance with optimal input variables and number of input variables and order. To evaluate the performance of the GAs-based FPNNs, the models are experimented with the use of Medical Imaging System(MIS) data.
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