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    混凝土强度无损检测数据处理的混沌优化神经网络模型

    Chaos Optimum and Neural Network Model for Data Processing in Nondestructive Testing of Concrete Intensity

    • 摘要: 依据混凝土标准试块强度检测数据,建立了混沌优化的神经网络计算模型,从而克服传统BP网络收敛速度慢、易出现麻痹现象等不足。与混凝土无损检测现行规程规定的方法相比较,该计算模型简单可行,搜索速度快,预测结果可靠、精度高。

       

      Abstract: A chaos optimum and neural network calculation model was built based on plenty of testing data of concrete intensity to cover the shortage of single BP neural network, such as slow astringency and easy torpidity. Compared with the algorithm stipulated in the current concrete nondestructive testing regulation, the model built was more simple and rapid for operation and higher in precision and reliability.

       

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