基于PCA-BP神经网络的尾矿库坝体稳定性分析

Analysis of the Stability for Mine Tailings Dam Based on PCA-BP Neural Network

基于尾矿库坝体稳定性影响因素具有复杂多变性、随机不确定性和非线性的特点,为了确保尾矿库稳定并且有效预防尾矿库事故的发生,建立了基于PCA和BP神经网络的尾矿库坝体稳定性研究模型,该模型通过应用SPSS软件对来自多个尾矿库失稳实例的原始数据进行标准化,找出影响尾矿库坝体稳定的主成分,然后把主成分作为BP输入样本,运用MATLAB软件进行训练仿真。结果表明:在BP训练前,利用PCA算法对原始样本进行预处理,能有效地提高训练的速度和精度,得出了PCA-BP神经网络模型在尾矿库坝体稳定性分析中是可行的。

The characteristics of the influence factors for the stability of mine tailings dam is complex variabily,uncertain and nonlinear.For the purpose of guaranteeing the stability of the tailings and preventing mine tailings dam accident effectively,an analysis model of the stability for mine tailings dam based on PCA-BP neural network is established.The original data from multiple mine tailings dam instability instance is standardized to determine the principle component by using SPSS software,then we use the principle component as a BP input sample to train simulation by using MATLAB software.The data shows that preprocessing the original sample by using PCA algorithm before the BP training can effectively improve the training speed and precision,the PCA-BP neural network model is feasible in the analysis of the stability for mine tailings dam.