DocumentCode
2606880
Title
Application of ANN to Prediction of Earthquake Influence
Author
Su, You-Po ; Zhu, Qing-jie
Author_Institution
Coll. of Civil Eng. & Archit., Hebei Polytech. Univ., Tangshan, China
Volume
2
fYear
2009
fDate
21-22 May 2009
Firstpage
234
Lastpage
237
Abstract
The maximum of earthquake affecting coefficient is a main parameter of earthquake response spectra, which is the key of seismic microzonation and design of earthquake resistant structures. Because the distribution of the maximum of earthquake affecting coefficient is controlled by basement rock and site condition, the relationship between the maximum of earthquake affecting coefficient and influencing factors is complicated. In order to design earthquake response spectra subtly, the calculating model is constructed on the basis of artificial neural network (ANN), which makes the parameter (the maximum of earthquake affecting coefficient) become a variable. In Tangshan City, the calamitous earthquake in 1976 deprived of 243,000 peoplepsilas lives, and more attention has been paid to seismic microzonation. As an example application, the distribution of the maximum of earthquake affecting coefficient is calculated precisely, and it is applied to the design of earthquake response spectra and seismic microzonation in Tangshan City. Finally, the calculating results are analysed and some advice is proposed for the city planning for disaster prevention.
Keywords
earthquakes; geophysics computing; neural nets; town and country planning; artificial neural network; basement rock; city planning; disaster prevention; earthquake affecting coefficient; earthquake influence prediction; earthquake resistant structure design; earthquake response spectra; seismic microzonation; site condition; Earthquakes; Tangshan; earthquake affecting coefficient; microzonation; response spectra; seismic;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Computing Science, 2009. ICIC '09. Second International Conference on
Conference_Location
Manchester
Print_ISBN
978-0-7695-3634-7
Type
conf
DOI
10.1109/ICIC.2009.169
Filename
5169053
Link To Document