摘要
以万州城区吴家湾滑坡为例,分析了神经网络(ANN)方法用于滑坡灾变识别的评价因子的确定、学习样本数据对的建立、ANN网络结构及参数设置的方法;并以万州区类似的滑坡作为样本训练ANN模型,对吴家湾滑坡的几种工况进行灾变识别.最后将ANN灾变识别结果与传统的极限平衡计算结果进行对比分析,得到了二者基本吻合的结果.结论表明神经网络方法用于滑坡灾变识别的精度较高,识别结果令人满意.
The paper aims at ANN disaster-possibility identifying of Wujiawan Landslide. ANN construction and parameter setup are analyzed for landslide disaster identifying by ANN, based on a typical landslide-Wujiawan landslide in Wanzhou urban, by confirming evaluation factor and establishing sample data. The ANN model is trained by the similar landslide sample in Wanzhou urban, then the disaster is identified in several different conditions of Wujiawan landslide. Finally, the same conclusion are found by analyzing combined ANN Disaster-Identifying and limit-equilibrium-method calculation. The results show that AAN is accurate and satisfied to be used landslide disaster-possibility identifying.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2005年第12期108-111,共4页
Journal of Chongqing University
基金
国家科技"十五"攻关课题(2001BA604A02)
重庆市高等学校优秀中青年骨干教师资助计划(渝教人[2005]2号)
重庆大学基础及应用基础项目(2003083)
重庆大学高层次人才启动基金(200518)资助
关键词
滑坡
灾变识别
神经网络
对比分析
landslide
disaster identifying
Nerve network
contrast analyzing
