水土保持通报2012，Vol.32Issue(5)：235-238,4.
滑坡变形的多因素小波神经网络预测模型
Multiple Factors Model for Landslide Deformation Prediction Based on Wavelet Neural Network
摘要
Abstract
Wavelet neural network has better approximation and fault-tolerance for combining the time-frequency localization of wavelet transform and self-study function of traditional neural network.We took some typical landslides in hydropower engineering region as an example and built three wavelet neural network models of multiple factors for landslide deformation prediction,on the basis of analyzing basic characteristics and the relationships between landslide deformation and main influencing factors of the landslide.By analyzing and comparing the results of the models,we found that the wavelet neural network model including the two factors(displacement rate and rainfall) has the highest prediction accuracy in the three models.关键词
滑坡/变形预测/小波神经网络模型/多因素Key words
landslide/deformation prediction/wavelet neural network model/multiple factor分类
天文与地球科学引用本文复制引用
李秀珍,王芳其..滑坡变形的多因素小波神经网络预测模型[J].水土保持通报,2012,32(5):235-238,4.基金项目
国家自然科学基金项目“基于小波分析的滑坡灾变预测方法研究” （）
