Application of Artificial Neural Networks and GIS in Urban Earthquake Disaster Mitigation

Author

Junjie, Wang ; Huiying, Gao ; Junfeng, Xin

Author_Institution

Environ. Sci. & Eng. Coll., Ocean Univ. of China, Qingdao, China

Volume

1

fYear

2010

fDate

11-12 May 2010

Firstpage

726

Lastpage

729

Abstract

An Artificial neural network analysis model for earthquake-damaged, which couples geographic information systems(GIS) with artificial neural networks (ANN) to predict the seismic damage to multistory buildings based on earthquake intensity and adopt the peak acceleration value, is presented here. ANN is used to learn the patterns of development in the region and test the predictive capacity of the model, while GIS is used to develop the spatial, and perform spatial analysis on the results. The ANN combined with GIS was found to have a great potential to predict seismic damage.

Keywords

earthquakes; geographic information systems; geophysics computing; learning (artificial intelligence); neural nets; seismology; GIS; artificial neural network analysis model; geographic information systems; pattern learning; peak acceleration value; seismic damage prediction; spatial analysis; urban earthquake disaster mitigation; Acceleration; Artificial neural networks; Earthquakes; Geographic Information Systems; Information analysis; Pattern analysis; Performance analysis; Performance evaluation; Predictive models; Testing; ANN; Geographic information system (GIS); Seismic prediction; structure vulnerability;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on

Conference_Location

Changsha

Print_ISBN

978-1-4244-7279-6

Electronic_ISBN

978-1-4244-7280-2

Type

conf

DOI

10.1109/ICICTA.2010.409

Filename

5523070