Based on GIS and Neural Network of the Geological Disaster Harm Division in the Western Region of the Himalayas

Abstract:

The hazard evaluation index system is divided into basic factors and vulnerability factors, According to the actual data collected in the Himalayas Geological Survey and the main factors index of geological disaster harm degree in study area were extracted in accordance with the evaluation index system. Using GIS to digitize, statistic, overlay, merge, classify and spatial analysis the basis of geological data. The weight of each evaluation factor can be exhibited according to the prediction to disaster survey points using BP neural network and the training and testing of the sample data using neural network inversion process, then the hazard evaluation to the research area can be processed by using this weight to have a direct overlay analysis. The regional hazard evaluation was completed using disaster points and area statistics. There is a realization of the evaluation unit grid, factor comparison, factor overlay, and an accomplishment of the facture about the thematic maps of evaluation results according to the secondary development of MAPGIS.

• Periodical: Applied Mechanics and Materials (Volumes 170-173)
• Pages: 1314-1317
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.170-173.1314
• Online since: May 2012
• Authors: Chong Liu, Gang Cheng Wang, Wen Ming Xu
• Keywords: Basic Factors, BP Neural Network (BPNN), Hazard Division, Vulnerability Factors

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