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《Sichuan Building Science》 2013-02
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Frost heaving prediction model in seasonal frost regions based on ANFIS

CUI Hongchuan1,XIANG Yiming2,SUN Xiaoxi1(1.Jilin Communications Planning and Design Institute,Changchun 130022,China; 2.School of traffic,Jilin University,Changchun 130021,China)  
Artificial intelligence technologies have been used in many areas in geotechnical engineering applications.Adaptive network-based fuzzy inference system(ANFIS) is proposed to forecast frost heaving in seasonal frozen regions.The fuzzy inference of ANFIS is initialized by subtractive clustering.The neural network is applied to adjust the parameter of the fuzzy inference system with hybrid algorithm and can produce fuzzy rules automatically.The data of frost heaving test obtained from a literature are used to train and check ANFIS network.The predicted results show that the proposed modeling approach is better than the back-propagation(BP) neural network in terms of computational speed,forecast errors,efficiency.ANFIS is an effective method to achieve both high accuracy and less computational complexity for predicting frost heaving.
【CateGory Index】: U212.22
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