The Analysis On Rock-Slope Stability Based On Genetic Algorithm

With the development of large-scale construction projects, more and more high and steep slopes have appeared in all kinds of construction fields, which are always essential factors in deciding whether the project is economical and reasonable or not. Therefore, how to design a slope project or evaluate the stability of a natural slope in an economical, safety and reliable way is of great significance. Among the methods of slope stability evaluation, Genetic Algorithm is a relatively effective one. As to this method, some researches about the slope stability evaluation by optimizing means were done by this thesis.Firstly, this thesis introduced the basic concepts of Genetic Algorithm, main characters and principles of self-organizing neural networks and Genetic Algorithms were also briefly discussed in the first part. Then the paper illuminated that how to take use of self-organizing neural networks in forecasting the stability of a slope and principal ways in optimizing the topological structure of Genetic Algorithms. Genetic Algorithm were learned through its classified samples, which led to improved learning efficiency and enhanced popularizing ability of networks. 0n the basis of above theories and methods, the thesis is developed on the base of Visual C++ 6.0 platform, through its experience on the object of Xiangshan fire-preventing-road, experimental results proved that the safety coefficient fitting as well as sample error of Lizheng professional slop stability analysis software had got distinct improvement after their optimization.Furthermore the thesis also analysis the influence of the elements that control the rock slope stability based on the Grey Correlation analysis, confirmed which element infect the most strongly on the stability of the rock slope. And also provide important directive on the rock slope stability analysis.