摘要
由于边坡岩体的结构与物理力学性质表现出宏观和微观上的不连续性和高度的非线性等特点,其稳定性受地质因素和工程因素等的综合影响,这些因素大部分具有随机性、模糊性、可变性等不确定性特点,因此,边坡工程是不确定的、非线性的、动态开放性的复杂大系统,传统分析方法往往难以准确地描述这种复杂的非线性特征,因而对大型复杂边坡的稳定性进行准确预测预报尚存在一定的困难。提出了基于模拟退火交替迭代算法神经网络的边坡安全系数预测方法,在相同的初始条件下,用该方法和经典网络进行了比较,得出前者的优越性和有效性。在综合分析边坡岩体变形失稳破坏模式及其影响因素的基础上,采用了表征边坡岩体稳定性分析的复合指标为预测模型的影响因子。并利用该方法对收集到的水电工程边坡实例进行学习,对未学习过的边坡实例进行推广预测,取得了较好的效果,其预测精度明显优于经典算法BP神经网络。由此说明所提出的预测模型能够快速、准确地获取不同方案下的边坡安全系数,为选择经济合理的边坡设计方案提供了新的思路。
The stability of slope is significant in civil engineering, and the structure and physical and mechanical properties of slope rock hold characteristics of macroscopic and microscopic discontinuity, high nonlinearity. The stability of slope is greatly affected by geological structure and its construction. However, these factors are random, fuzzy and changeable, so the slope is an uncertain, nonlinear, dynamic and complicated system; and it is difficult to describe such nonlinear characteristics of this system with traditional methods. Therefore, the stability of large and complicated rock slopes could not be accurately forecasted. A novel forecasting method, which is an alternation and iterative algorithm based on simulated annealing applied in neural network（NN） is presented. Under the same initial conditions, the comparison of the new method with the traditional NN algorithm is conducted; and the result shows the superiority and efficiency of the former. Based on comprehensively analyzing the mechanism of stability loss of rock slopes and the main factors affecting the stability of rock slopes, the compound indices were proposed for forecasting model as influencing factors. Then, the cases of rock slopes in hydropower projects are taken as training samples and the unlearning cases are forcast; and the results is satisfying, showing that the forecasting accuracy is superior to traditional BP neural network. Therefore, the forecasting model put forward here can get safety factor of different rock slopes quickly and accurately; and it can provide a new approach for selecting slope design economically and rationally.
出处
《岩石力学与工程学报》
EI
CAS
CSCD
北大核心
2005年第19期3492-3498,共7页
Chinese Journal of Rock Mechanics and Engineering
关键词
边坡工程
非线性
模拟退火
交替迭代算法
复合指标
预测
slope engineering
nonlinearity
simulated annealing
alternation and iterative algorithm
compound indices
forecasting
