Seismic damage prediction of multistory building using GIS and Artificial neural network

Author

Wang, Jun-Jie ; Gao, Hui-Ying ; Liu, Ming-Qiong

Author_Institution

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

Volume

4

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

1821

Lastpage

1824

Abstract

An integrated GIS and 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

building; earthquakes; geographic information systems; neural nets; seismology; ANN; artificial neural network; earthquake damage; earthquake intensity; geographic information system; integrated GIS; multistory building; peak acceleration value; seismic damage prediction; spatial analysis; Acceleration; Artificial neural networks; Buildings; Cities and towns; Earthquakes; Geographic Information Systems; Neurons; ANN; Geographic information system (GIS); Seismic prediction; structure vulnerability;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2010 Sixth International Conference on

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-5958-2

Type

conf

DOI

10.1109/ICNC.2010.5584603

Filename

5584603