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| Study on Prediction of Bearing Capacity of CFG Pile Composite Foundation with ANFIS |
| XUE Xin-hua,WEI Yong-xing |
| China Railway Eryuan Engineering Group Co. Ltd,Chengdu, Sichuan 610031, China |
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Abstract Research purposes：The main factors influencing the bearing capacity of CFG pile composite foundation are the parameters of CFG pile; replacement rate, physical mechanical characteristics of soil, cushion thickness and construction technique, and the various factors mentioned above have highly complex non-linear relationship, so it is rather difficult to determine the bearing capacity of CFG pile composite foundation. To reasonably and accurately predict the CFG pile composite foundation's bearing capacity, the adaptive-network based on fuzzy inference system was proposed.
Research conclusions：The theory of adaptive-network-based fuzzy inference systems (ANFIS) was introduced and subtractive cluster method was applied to deciding fuzzy inference rules. After that, an ANFIS was used to predict the bearing capacity of CFG pile composite foundation. The predicted results show that the adaptive fuzzy neural network has higher accuracy and adaptability than the BP network and least squares support vector machines LS-SVM model, and it provides a new approach to predict the bearing capacity of CFG pile composite foundation.
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Received: 16 January 2010
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2010, Vol. 27 
