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Abstract: The idea of fuzzy optimization is introduced in the
optimization of cold extrusion mold process parameters. An approach of
fuzzy optimization of cold extrusion mold process parameters based on
genetic algorithm and multiplayer neural network is presented. Firstly,
the fuzzy optimization model of cold extrusion mold is introduced.
Secondly, the fuzzy optimization strategy using genetic algorithm and
multiplayer neural network is discussed, including constructing an
approximate model with artificial neural networks and solving the fuzzy
optimization model using genetic algorithms. In constructing fitness
function, the weight factors are determined by orthogonal numerical
experiments. Finally, the optimization results demonstrate the fuzzy
optimization method can improve the quality of the cold extrusion mold.
Key words: Genetic algorithm Fuzzy optimization Neural network
Optimization of cold extrusion mold process parameters Orthogonal
numerical experiments
CLC No: TH122
教育部优秀青年教师基金、国家自然科学基金(60175019)和上海市高等学校青年科学基金资助项目
. Received 20010416, received in revised form 20010828
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