【摘 要】
：
Machine learning has been extensively applied in various fields of engineering including image processing,automatic control,etc.Binary decision tree (BDT),support vector machine (SVM),artificial neura
【机 构】
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Dept.of Architecture and Architectural Engineering, Kyoto University, Kyoto 615-8540, Japan
【出 处】
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Asian Congress of Structural and Multidisciplinary Optimizat
论文部分内容阅读
Machine learning has been extensively applied in various fields of engineering including image processing,automatic control,etc.Binary decision tree (BDT),support vector machine (SVM),artificial neural network (ANN),and association rule are the basic tools of machine learning.However,only a few studies can be found for application of machine learning to structural optimization.In 1990s,ANN was extensively used mainly for estimating the structural responses in the process of structural optimization.For example,nonlinear seismic responses of a 3D-frame were estimated;the maximum stress ratio of a plate composed of functionally graded material was estimated;and a basic framework of structural optimization based on estimation of constraint functions was proposed.Biedermann and Grierson[l]trained member grouping in the process of optimization of plane frames.However,most of the applications were for estimation of function values rather than classification of solutions that can be a candidate of approximate optimal solution.Furthermore,most of applications of ANN are in the second generation,when application to only small toy problems were possible.
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