학술논문
A neural network method for risk assessment and real-time early warning of mountain flood geological disaster
Document Type
Conference
Author
Source
2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Intelligent Signal Processing and Communication Systems (ISPACS), 2017 International Symposium on. :540-544 Nov, 2017
Subject
Language
Abstract
Zhongshan County of Guangxi Zhuang Autonomous Region was selected as the study area to investigate the intelligent assessment and early warning system of mountain flood geological disaster. Remote sensing images, spectral data and DEM data were processed on ENVI and ArcGIS platforms and the quantized data including slope, NDVI, soil looseness coefficient, valley and ridge classification and rainfall were obtained. And then a generalized regression neural network model for risk assessment of mountain flood geological disaster in Zhongshan County was established with the above quantized data as the input factors and the risk degree of the mountain flood geological disaster as the output factor. The trained model by using historical data has an excellent self-learning function and provide a good prediction on the risk degree of the mountain flood geological disaster in Zhongshan County.