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- W162524897 abstract "The performance of complex system are reflected by various factors, which is difficult to obtain the accurate mathematic model. While in order to enhance the quality of products, the optimal and robust value of inflected factors are needed. Aimed at the robust optimatization of complex system without objective function, a novel combined approach is presented. Firstly, the mathematic expression between performance and factors is obtained by neural network. After that the mapping relationship between the performance and the difference of factors is induced by gradient method and lagrange multiplier method, which corresponds to the senstivity of factors changing to performance. On the basis, the novel fitness fuction of robust optimization is built up with actual subject condition. In the end, the robust value which are insenstive to performance can be searched by genetic algorithm. According to the robust optimization design of single valve amplified circuit, the optimization methodology is verfied to be optimal and robust comparied with the results of traditional fitness function.KeywordsRobustoptimizationgradientlagrange multiplierneural networkgenetic algorithm" @default.
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- W162524897 date "2009-01-01" @default.
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- W162524897 title "A Novel Approach to Robust Optimization of Complex System without Objective Function" @default.
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- W162524897 doi "https://doi.org/10.1007/978-3-642-03664-4_95" @default.
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