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基于演化算法的桩基极限承载力预测模型研究
Research in Prediction Model of Ultimate Bearing Capacity of Piles Based on Evolutionary Computation Algorithm
【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。
【Abstract】 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 algorithm called particle swarm optimization, prediction model 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.
【Key words】 pile foundation; ultimate bearing capacity; BP neural networks; particle swarm optimization algorithm;
- 【文献出处】 重庆建筑 ,Chongqing Architecture , 编辑部邮箱 ,2005年09期
- 【分类号】TU473.11
- 【被引频次】2
- 【下载频次】88