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

Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010

Volumn 4, Issue , 2010, Pages 1821-1824

  Wang, Jun Jie ^a   Gao, Hui Ying ^a   Liu, Ming Qiong ^a  

^a OCEAN UNIVERSITY OF CHINA   (China)

Author keywords

ANN; Geographic information system (GIS); Seismic prediction; Structure vulnerability

Indexed keywords

EID: 78149305141     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNC.2010.5584603     Document Type: Conference Paper

References (9)

1. Baaske, P., Mutti, M., Baioni, F., Bertozzi, G. & Naini, M. A. (2007). Using multiattribute neural networks classification for seismic carbonate facies mapping; aworkflow example from Mid-Cretaceous Persian Gulf deposits (in seismicgeomorphology; applications to hydrocarbon exploration and production) (Vol.277, pp. 105-120). Geological Society Special Publications.
2. Bastian, A. (2000). Identifying fuzzy models using genetic programming. Fuzzy Sets and Systems, 113, 333-350.
3. ESRI Corp. ArcGIS Engine Developer Guide.
4. Chang, T. K., Yu, D. L., & Yu, D. W. (2004). Neural network model adaptation and its applications to process control. Advanced EngineeringInformatics, 18, 1-8.
5. Liu Chun-Guang, DU Wei, CUI Tong. Seismic reliability of urban transportation systems [J]. Dalian University of Technology, 2002, 24 (7) :1-64.
6. Kuo, R. J., Hong, S. M., Lin, Y., & Huang, Y. C. (2008). Continuous genetic algorithmbased fuzzy neural network for learning fuzzy IF-THEN rules. Neurocomputing, 71(13-15), 2893-2907.
7. Linkens, D. A., & Nyongesa, H. O. (1995). Genetic algorithms for fuzzy control - Part1: Off-line system development and application. IEE Proceedings Control Theory and Applications, 142(3), 161-176.
8. MIAO Sheng, LIU Ben-yu, YE prairie fire. Multistory masonry seismic damage prediction based on artificial neural network method and practice [J]. World Conference on Earthquake Engineering, 2000, 16 (1): 21 - 27.
9. Tang, A. M., Quek, C., & Ng, G. S. (2005). GA-TSKfnn: Parameters tuning of fuzzy neural network using genetic algorithms. Expert Systems with Applications, 29(4), 769-781.1986.