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Alternative TitleResearch of Landslide Risk Assessment Based on BP Neural Network
王萌1,2,3; 乔建平1,3; 石莉莉1,2,3
Corresponding Author王萌
Source PublicationInternational Conference on Engineering and Business Management(EBM2010) ; Proceedings of International Conference on Engineering and Business Management(EBM2010)
Conference Date2010-3-25
Conference Place四川成都
Funding Organization武汉大学;美国James Madison大学;美国科研出版社
性评价的研究特点。因此本文应用GIS 技术和BP 神经网络相结合的方法,以重庆市万州区为示
度。因此利用BP 神经网络进行滑坡风险性评价具有可行性。
Other AbstractThe inducing factors of landslide are numerous. Commonly, they have nonlinear relationship with landslide risk. Current methods cannot meet the needs of evaluating landslide risk. The artificial neural network which is developing in recent years belongs to a kind of nonlinear dynamic system and has characteristics which can be fit for landslide risk assessment. This work presents the result of applying the GIS technology and BP neural network in establishing the process of regional landslide risk assessment with Wanzhou district of Chongqing city as the study area. Based on the standard of landslide risk classification, learning sample set was set up. Subsequently, the complicated nonlinear relationship between regional landslide risk grades and inducing factors was established by neural network self-study ability. The result shows that the sample set of Wanzhou district is convergent well in BP neural network and the trained one has higher recognition and reliability. Consequently, the method is feasible for landslide risk assessment.
KeywordBp神经网络 滑坡 风险性评价
Document Type会议论文
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
王萌,乔建平,石莉莉. 基于BP神经网络的滑坡风险性评价研究[C],2010:5343-.
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