Title :
Predictive Model of Artificial Neural Network for Earthquake Influence Analysis
Author :
Yanhua, Chen ; Tingquan, Liu ; Weiwei, Liu
Author_Institution :
Coll. of Civil Eng. & Archit., Hebei Polytech. Univ., Tangshan, China
Abstract :
Earthquake affecting coefficient is a main parameter of earthquake response spectra, which is the foundation of seismic microzonation and design of earthquake resistant structures. Because the distribution of the maximum of earthquake affecting coefficient is controlled by both 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 predictive model is constructed on the basis of artificial neural network (ANN), which makes the distribution of the maximum of earthquake affecting coefficient become a spatial variable. As an example application in Tangshan City, the distribution of the maximum of earthquake affecting coefficient is calculated precisely. The calculating results are analyzed and some advice is proposed.
Keywords :
earthquakes; geophysics computing; neural nets; Tangshan City; artificial neural network; earthquake affecting coefficient; earthquake influence analysis; earthquake resistant structures; predictive model; seismic microzonation; Artificial neural networks; Buildings; Cities and towns; Civil engineering; Earthquakes; Educational institutions; Information technology; Predictive models; Sediments; Stress; earthquake affecting coefficient; microzonation; predictive model; response spectra;
Conference_Titel :
Information Technology and Applications, 2009. IFITA '09. International Forum on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3600-2
DOI :
10.1109/IFITA.2009.346
