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Model optimization of load - bearing capacity of macadam pile composite foundation based on genetic algorithm

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5 Author(s)
Meixia Liu ; Dept. of Water Conservancy Eng., Agric. Univ. of Hebei, Baoding ; Zhihong Qie ; Xinmiao Wu ; Wenwen Dong
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In this paper, model optimization method of load - bearing capacity of composite foundation based on genetic algorithm is put forward. In this method, the chromosome bit string, which is looked as the generator, is used to complete random combination of influence factor and therefore need not be decoded. Considering both the fitting accuracy to modeling data and prediction accuracy to other data, model samples are divided into training samples and checkout samples, and in order to the balance between fitting accuracy and prediction accuracy, the multiple regression function is built and optimized. Through analyzing the static load experiment data of fifteen vibrating macadam pile, the genetic regression model of bearing capacity of macadam pile composite foundation is established, the prediction result shows, that the method has good fitting accuracy and predict accuracy and the stability of the model is satisfactory.

Published in:

Control and Decision Conference, 2008. CCDC 2008. Chinese

Date of Conference:

2-4 July 2008