基于进化支持向量机的滑动面参数识别

基于进化支持向量机的滑动面参数识别 English Version

基金项目: 中国科学院武汉岩土所岩土力学重点实验室开放基金资助项目(Z110405);;浙江省高校青年教师资助计划;;绍兴市科技计划项目(2004146)

1.Key Laboratory of Rock and Soil Mechanics Institute of Rock and Soil Mechanics Chinese Academy of Sciences Wuhan 430071 China 2.Department of Civil Engineering Shaoxing University Shaoxing 312000 China

摘要: 提出了反算滑带岩土强度参数的一种新方法——进化支持向量机方法,该方法基于极限平衡分析方法计算出不同c、值下的安全系数与最危险滑动面,以这些数据作为学习样本,通过支持向量机学习,建立他们之间的非线性映射关系,然后基于这种关系,利用遗传算法搜索滑带岩土强度参数。结果表明,识别出的c、值可以满足工程的要求。
- 滑坡 /
- 极限平衡原理 /
- 支持向量机 /
- 反分析 /
- 遗传算法
Abstract: A new method to back-calculate the strength parameters of landslide using genetic-support vector machine was proposed.Critical slip surfaces and minimum factors of safety were determined with different combinations of c and  using limited equilibrium analysis.The nonlinear relationship between c, and minimum factors of safety were established using support vector machine.The strength parameters of landslide were recognized based on this relationship.It was shown that the c and  values were sufficiently accurate for engineering applications.
- landslide /
- limited equilibrium theory /
- support vector machine /
- back analysis /
- genetic algorithm