摘要
针对BP神经网络易收敛慢、易陷入局部极小等不足,引入遗传算法处理了BP的初始权值和阈值,并在此基础上建立了长螺旋压灌混凝土桩复合地基单桩极限承载力预测模型。利用该模型通过对现场工程数据进行了学习、训练以及预测检验。预测结果精度高,表明此模型是有效的,并在单桩承载力预测方面具有较好的应用价值。
In order to overcome the defect of the low convergence rate and local minimal of BP neural network,genetic algorithm was introduced to deal with the initial weight values and threshold in BP neural network algorithm.Based on the combination of genetic algorithm and BP neural network,the bearing capacity prediction model of single pile was built up,and the model was learned,trained and tested by a known engineering data,the prediction result was perfect and showed that the model was feasible and effective fo...
出处
《武汉理工大学学报》
EI
CAS
CSCD
北大核心
2008年第3期86-89,共4页
Journal of Wuhan University of Technology
基金
湖北省建设厅科技项目(K200549)
关键词
复合地基
单桩承载力
遗传算法
BP神经网络
composite foundationl
bearing capacity of single pile
genetic algorithm
BP neural network