The Study of Areas Prone to Geological Hazards in Ningde Based on ANN and AHP

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Research areas:
Year:
2018
Type of Publication:
Article
Keywords:
Water Demand Prediction, Neural Network, Hazards Assessment, AHP
Authors:
Shiliang Zhang
Journal:
IJAIM
Volume:
6
Number:
6
Pages:
71-76
Month:
May
ISSN:
2320-5121
Abstract:
In recent years, with the advance of development, various human activities on geological engineering increasingly serious environmental damage, accompanied by the flow of a large number of landslides and other geological disasters occur. In order to coordinate the work of regional hazards prevention and reduction, This article utilizes the geological risk assessment analysis which combines GIS technology and the artificial neural network model, introducing the powerful GIS visualization of spatial information management and analysis along with the nonlinear description and analysis function of the neural networks to achieve the visual management of geological hazard evaluation in Ningde city, based on the collection data and field survey in the study area. It can be concluded that AHP is an easy applicable and appropriate tool to rank Geological Hazards schemes with respect to the scale considering social, economic and environmental issues. This has important significance for improving governance and prevention of geological disasters information
Full text: IJAIM_604_FINAL.pdf

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