小净距隧道开挖围岩压力的混沌神经网络模型预测

Pressure Prediction of Surrounding Rock in Tunnel Based on Chaotic Neural Network

隧道围岩压力是分析围岩稳定性的关键因素。由于围岩变形受众多因素影响,且各因素之间存在强烈的非线形关系,因此,难以进行有效的预测。提出基于混沌神经网络模型的方法,分析混沌与神经网络相结合预测手段的可行性,对围岩随时间变化的压力进行仿真计算。对该理论的建立及预测方法进行系统分析,为该领域的研究提供有效的技术方法。结果表明,此方法预测精度高,能够满足工程及控制要求。

The surrounding rock pressure is key to analyze the stability.However,the displacement of surrounding rock influenced by so many factors,and there is nonlinear function between those factors,so it is difficult to estimate.This article present a method of chaotic neural networks for simulation of surrounding rock pressure by time series and analyses feasibility of forecasting by using chaos neural network,The establishment of the prediction model and the process of application are discussed in detail.The result indicated that this method is efficient and feasible,on the certain degree;this method is fit to engineering control.