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標題: 使用資料挖掘類神經網路和演化策略之全域最佳化方法
The global optimization method using data mining, artificial neural network and evolution strategy
作者: 鄭義良
Cheng, Yi-Liang
關鍵字: data mining;資料挖掘;artificial neural network;evolution strategies;類神經網路;演化策略法
出版社: 機械工程學系所
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The evolutionary algorithm has a general capability to solve all kinds of problems and is easier to find the global solution. But due to a huge number of function evaluations it is hard to be applied to complex engineering optimization problems. Therefore this thesis proposes an approach of integrating data mining, artificial neural network and evolution strategy to solve structural optimization problems. The data mining will be used to separate the feasible region from the infeasible one in order to reduce the searching space and hence increase the probability of finding global solution. The neural network is created to replace the exact finite element analysis to save computational time. An external elite set keeps some best designs when ES search is completed. A mathematical programming method is used to find exact global solution from there elite designs. For most test problems the proposed approach finds global solutions and for some problems the cpu time consumed by this proposed method is much less than that by other methods.
其他識別: U0005-1001200704080800
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