改进粒子群算法+BP神经网络在边坡可靠度分析中的应用  

Application of Improved Particle Swarm Algorithm+BP Neural Network in Slope Reliability Analysis

作　　者：徐小兵 XU Xiaobing(Zhijiang Dong Autonomous County Traffic Construction Quality and Safety Supervision Station,Huaihua,Hunan 419100,China)

机构地区：[1]芷江侗族自治县交通建设质量安全监督站,湖南怀化419100

出　　处：《黑龙江交通科技》2024年第8期41-45,共5页Communications Science and Technology Heilongjiang

摘　　要：为准确计算高边坡的稳定可靠度,提出了一种基于改进粒子群算法+BP神经网络的边坡可靠度分析方法。通过BP神经网络建立了高边坡神经网络模型,采用改进粒子群算法对边坡稳定系数进行了求解。结果表明:改进粒子群算法在不同测试函数的寻优精度最高;BP神经网络预测结果较好;该方法计算得到的边坡稳定可靠度相较于其他方法较小,计算结果偏于保守。In order to accurately calculate the stability reliability of high slope,a slope reliability analysis method based on improved particle swarm optimization algorithm and BP neural network is proposed.The BP neural network model of high slope is established,and the improved particle swarm optimization algorithm is used to solve the slope stability coefficient.The results show that the improved particle swarm optimization algorithm has the highest optimization accuracy in different test functions;The prediction results of BP neural network are good;Compared with other methods,the slope stability reliability calculated by this method is smaller,and the calculation result is conservative.

关 键 词：BP神经网络 粒子群算法 边坡可靠度 稳定系数 

分 类 号：U417.1[交通运输工程—道路与铁道工程]