Research on Regional Flood Disaster Risk Assessment Based on PCA and BP Neural Network

Author

Jin, Qiongji ; Chen, Junfei ; Wang, Huimin ; Zhao, Shufang

Author_Institution

State Key Lab. of Hydrol.-Water Resources & Hydraulic Eng., Hohai Univ., Nanjing, China

fYear

2010

fDate

7-9 Nov. 2010

Firstpage

1

Lastpage

4

Abstract

Flood disaster management is an important part of flood risk assessment. A regional flood disaster risk assessment index system is established in this paper. Then principal component analysis (PCA) method and BP neural network are combined, and a regional flood disaster risk assessment of PCA-BP neural network model is established. PCA-BP neural network model analyze the loss of flood disaster about 30 China´s provinces and cities in 2006 to assess the regional flood disaster risk, the results of the assessment are in line with actual situation, the flood disaster risk assessment model which is established in this paper is valid.

Keywords

backpropagation; disasters; floods; neural nets; principal component analysis; public administration; risk management; 30 Chinas provinces; BP neural network; PCA; principal component analysis; regional flood disaster risk assessment; risk assessment index system; Analytical models; Artificial neural networks; Biological system modeling; Floods; Indexes; Principal component analysis; Risk management;

fLanguage

English

Publisher

ieee

Conference_Titel

E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on

Conference_Location

Henan

Print_ISBN

978-1-4244-7159-1

Type

conf

DOI

10.1109/ICEEE.2010.5660290

Filename

5660290