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Study on Parameter Distribution in Structure Reliability Analysis: Machine Learning Algorithm and Application

机译:结构可靠性分析参数分布研究:机器学习算法与应用

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The discrimination of parameter probability distribution type is the key to structure reliability analysis. A support vector machine (SVM) intelligent recognition model of probability distribution law is presented aiming at traditional method disadvantage. The intelligent recognition model of probability distribution is constructed by SVM algorithm realization, network design and feature extraction, inward stress probability distribution type of a stem structural member is recognized by the model, recognition result is Weibull distribution, SVM has a good generalization ability and clustering ability by comparison between network recognition result and regression analysis, the experiment result shows total recognition rate achieved 98.25%, it provides a good new method for structure reliability analysis.
机译:参数概率分布类型的辨别是结构可靠性分析的关键。概率分布法的支持向量机(SVM)智能识别模型旨在旨在传统方法缺点。概率分布的智能识别模型由SVM算法实现,网络设计和特征提取,阀杆结构构件的向内应力概率分布类型被模型识别,识别结果是威布尔分布,SVM具有良好的泛化能力和聚类通过比较网络识别结果和回归分析的能力,实验结果表明了总识别率为98.25%,为结构可靠性分析提供了良好的新方法。

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