摘要
单桩的竖向极限承载力受众多因素的影响,各影响因素与单桩承载力之间存在着高度的复杂性和非线性,借助神经网络的一个非线性处理能力,结合演化算法,建立基于粒子群算法和BP神经网络的单桩竖向极限承载力的预测模型。实验结果表明,经过演化算法优化的BP神经网络,在预测精度和收敛速度上都取得了良好效果。
Ultimate bearing capacity of single pile was affected by some factors, ultimate bearing capacity of single pile and each influence factor has high complexity and non-linearity. With the help of nonlinear process ability of neural networks, companied with evolutionary algo- rithm called particle swarm optimization, prediction mod- el of vertical ultimate bearing capacity of single pile was established. The experimental result indicated, the BP neural networks optimized by particle swarm optimization algorithm, has obtained the good effect in the forecast precision and the convergence.
出处
《重庆建筑》
2005年第9期27-31,共5页
Chongqing Architecture
关键词
桩基础
极限承载力
BP神经网络
粒子群优化
pile foundation
ultimate bearing capacity
BP neural networks
particle swarm optimization algorithm