Mountain torrent disaster risk division and prediction method based on GIS (geographic information system)-neural network integration

A technology of neural network and prediction method, which is applied in the field of mountain torrent disaster risk zoning and prediction based on GIS-neural network integration, and can solve problems such as the uncertainty of the spatial scale of mountain torrent disaster assessment

Active Publication Date: 2018-07-13
SUN YAT SEN UNIV
View PDF2 Cites 39 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art, provide a kind of mountain torrent disaster risk zoning and prediction method based on GIS-neural network integration, build the mountain torrent disaster risk assessment and loss estimation model, solve the mountain torrent disaster assessment under the changing environment The problem of spatial scale uncertainty in

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Mountain torrent disaster risk division and prediction method based on GIS (geographic information system)-neural network integration
  • Mountain torrent disaster risk division and prediction method based on GIS (geographic information system)-neural network integration
  • Mountain torrent disaster risk division and prediction method based on GIS (geographic information system)-neural network integration

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0093] Such as Figure 1 to Figure 3 As shown, a method for zoning and forecasting of mountain torrent disaster risk based on GIS-neural network integration, which includes the following steps:

[0094] Step 1: The present invention selects Guangdong Province as the experimental area. Guangdong Province is located in the southern part of mainland China, with complex and diverse landform types, and is dominated by mountains and hills. Mountains above 500m above sea level account for 31.7%, and hills account for 28.5%. In addition, it is located in the subtropical monsoon region, with frequent rainstorms, affected by various natural and human factors such as special natural geographical environment, increasingly extreme disastrous weather, and human economic and social activities in mountainous areas, resulting in frequent mountain torrent disasters in Guangdong Province. Therefore, in order to further improve the defense work of mountain torrent disasters, the present inventio...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a mountain torrent disaster risk division and prediction method based on GIS (geographic information system)-neural network integration. The method includes the steps: S1 mining the association relationship between a risk factor and a risk grade in a mountain torrent disaster by the aid of association rules, identifying the risk factor and building a quantitative mountaintorrent disaster risk evaluation index system; S2 determining risk and vulnerability index system by an analytic hierarchy process and the weight of the system to generate feature layers; S3 stackingmountain torrent disaster risk and vulnerability distribution layers by ArcGIS to obtain a mountain torrent disaster risk distribution diagram; S4 performing clustering by an ISO maximum likelihood method, merging regions from bottom to top and performing qualitative analysis from top to bottom to form mountain torrent disaster risk division; S5 analyzing non-linear relationships among evaluationindexes, the risk grade and disaster data by an Elman neural network, and building a mountain torrent disaster risk evaluation and loss prediction model. The problem of spatial scale uncertainty in mountain torrent disaster evaluation in a changing environment can be solved, and the method can be widely used for evaluating mountain torrent disaster risks.

Description

technical field [0001] The invention relates to the field of mountain torrent disaster prevention and control, and more specifically, to a method for zoning and predicting mountain torrent disaster risk based on GIS-neural network integration. Background technique [0002] my country is a mountainous country, and the mountain area accounts for about 2 / 3 of the country's land area. The complex terrain and geological conditions, the climatic characteristics of frequent rainstorms, the dense population distribution and the influence of human activities lead to frequent occurrence of mountain torrent disasters. my country's mountain torrent disasters present the overall characteristics of wide range of influence, high frequency of occurrence, short duration of disaster, large degree of damage and significant regional differences. According to the statistics of the "National Mountain Flood Disaster Prevention and Control Planning Report", the watershed area of ​​my country's hil...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06N3/08
CPCG06N3/08G06Q10/04G06Q10/0635G06Q10/06393Y02A10/40
Inventor 林凯荣李文静梁汝豪
Owner SUN YAT SEN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap