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Based on GIS and neural network of the geological disaster harm division in the western region of the Himalayas

机译:基于喜马拉雅西部地区地质灾害划分的GIS和神经网络

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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.
机译:根据喜马拉雅山地质调查所收集的实际数据,危险评估指标体系分为基本因素和脆弱因素,并根据评价指标体系提取了研究区地质灾害危害程度的主要因素指标。使用GIS向数字化,统计,覆盖,合并,分类和空间分析地质数据的基础。每个评估因子的重量可以根据使用BP神经网络的预测和使用神经网络反演过程的样本数据的训练和测试来表现出对灾害调查点的预测,然后可以通过使用此处理对研究区域的危害评估重量具有直接叠加分析。利用灾害点和面积统计完成区域危害评估。根据MAPGIS的二次开发,有一个评价单元网格,因子比较,因子覆盖,以及关于评估结果的专题地图的构成。

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