Title :
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
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;
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
DOI :
10.1109/ICICTA.2010.409
