(1.Northwest Research Institute Co. Ltd of C. R. E. C，Lanzhou，Gansu 730000，China; 2.CREEC (Northwest) Survey and Design Co. Ltd，Lanzhou，Gansu 730000，China)
Abstract：Abstract ： Research purposes ： The effect of pile foundation is improving the bearing capacity of foundation and effectively reducing the settlement of structures. Pile foundation is in a variety of forms， and it can be applied to a variety of different stratums，can be widely applied to buildings which have strict request for settlement， buildings in which live load is big proportion of the total load， and other structures with special requirements for foundations. The quality of pile foundation inspection work and the reliability of evaluation results is an important link to ensure the safety and the quality of the pile foundation engineering. This paper effectively integrates the theory of pile foundation bearing capacity and experimental data with analytic hierarchy process and neural network theory，establishes neural network model for prediction of pile ultimate bearing capacity， to make the solution of bearing capacity of pie more fast， convenient and accurate. Research conclusions ：( 1) In engineering stations，the test of single pile vertical static load up to 1 500 t is rare，so successful field tests and accurate test results is the prerequisite for the effective combination of test data and neural network theory. (2) The application of artificial neural networks in geotechnical engineering makes effective solution of complex and fuzzy nonlinear problems. It has valuable reference significance on pelting on more improvement $ perfection and research work in this field. (3) The effective combination of pile bearing capacity theories and experimental data with analytical hierarchy process and neural network theory i an effective new way to solve thetest and calculation of large tonnage pile bearing capacity. (4 ) This research conclusion can provide guidance and reference for similar test and calculation of large tonnage pile bearing capacity.
崔雍,楚小刚,董嘉,靳月清,谭冬生. 基于神经网络的桩基竖向承载力预测研究[J]. 铁道工程学报, 2016, 33(4): 65-69.
CUI Yong1，CHU Xiao - gang1，DONG Jia1，JIN Yue - qing1，TAN Dong - sheng2. Prediction Research on the Vertical Bearing Capacity of Pile Foundation Based on Neural Network. Journal of Railway Engineering Society, 2016, 33(4): 65-69.
2016, Vol. 33 
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