Expert System Approach for Soil Structure Interaction and Land Use
Publication: Journal of Urban Planning and Development
Volume 136, Issue 2
Abstract
The application of expert systems has emerged as a cost efficient tool in civil engineering over the past decades. Use of these tools for decision making in land use will be outlined in this paper. In this study, soil-structure interaction (SSI) is discussed by using expert systems, namely, neural network (NN) approaches. This method provides a new point of view for evaluations of SSI and land use. Data from 58 local sites in California, namely, earthquake, structure, and soil property data, are used. In the expert system approach, two NN architectures are used: the back propagation NN architecture and the general regression NN (GRNN) architecture. There are 21 parameters considered as input and 4 output parameters. The four output parameters chosen are soil-to-structure rigidity ratio, period lengthening, foundation damping, and whether SSI effects can be neglected or not. The results show that the GRNN approaches are more useful and powerful for evaluation of SSI and land use.
Get full access to this article
View all available purchase options and get full access to this article.
References
Applied Technology Council (ATC). (1978). “Tentative provisions for the development of seismic regulations for buildings: A cooperative effort with the design profession, building code interests, and the research community.” Rep. No. ATC 3-06, U.S. Dept. of Commerce, National Bureau of Standards, Washington, D.C.
Building Seismic Safety Council (BSSC). (1997). “NEHRP recommended provisions for seismic regulations for new buildings. Part 1: Provisions and Part 2: Commentary.” Rep. No. FEMA 302&303, Federal Emergency Management Agency, Washington D.C.
Chopra, A. K., and Gutierrez, J. A. (1973). “Earthquake analysis of multistory buildings including foundation interaction.” Rep. No. EERC 73-13, Earthquake Engineering Research Center, Univ. of California, Berkeley.
Dayhoff, E. J. (1990). Neural network architecture: An introduction, Van Nostrand Reinhold, New York.
Dobry, R., and Gazetas, G. (1986). “Dynamic response of arbitrarily shaped foundations.” J. Geotech. Engrg., 112(2), 109–135.
Fenves, G. L., and DesRoches, R. (1994). “Response of the northwest connector in the Landers and Big Bear earthquakes.” Rep. No. UCB/EERC-94/12, Earthquake Engineering Research Center, Univ. of California, Berkeley, Calif.
Frederick, M. D. (1996). NEUROSHELL2 user’s manual: Version 3.0, Ward Systems Group.
Frost, J. D. (1997). “Spatial analysis in soil dynamics and earthquake engineering.” ASCE Geotech. Spec. Publ., 67, 144 .
Goh, A. T. C., and Chua, C. G. (2003). “Quantifying uncertainty in predictions using a Bayesian neural network.” Proc., 2nd MIT Conf. Computational Fluid and Solid Mechanics, GALAYAA B.V./MIT2_453, Elsevier, New York, 1–3.
Goh, A. T. C., Kulhawy, F. H., and Chua, C. G. (2005). “Bayesian neural network analysis of undrained side resistance of drilled shafts.” J. Geotech. Geoenviron. Eng., 131(1), 84–93.
Hanna, A. M., Ural, D., and Saygili, G. (2007a). “Evaluation of liquefaction potential of soil deposits using artificial neural networks.” Eng. Comput., 24(1), 5–16.
Hanna, A. M., Ural, D., and Saygili, G. (2007b). “Neural network model for liquefaction potential in soil deposits using Turkey and Taiwan earthquake data.” Soil Dyn. Earthquake Eng., 27(6), 521–540.
International Conference of Building Officials (ICBO). (1997). Uniform building code, International Code Council, Washington, D.C.
Jennings, P. C., and Bielak, J. (1973). “Dynamics of building-soil interaction.” Bull. Seismol. Soc. Am., 63, 9–48.
Kartam, N., Flood L., and Garrett, J. H. (1997). Artificial neural networks for civil engineers: Fundamentals and applications, ASCE, Reston, Va.
Kramer, S. L. (1996). Earthquake geotechnical engineering, International Series in Civil Engineering Mechanics, Prentice-Hall, Englewood Cliffs, N.J.
Seed, R. B., et al. (1990). “Preliminary report on the principal geotechnical aspects of the October 17, 1989 Loma Prieta earthquake.” Rep. No. UCB/EERC-90/05, Earthquake Engineering Research Center, Univ. of California, Berkeley, Calif.
Specht, D. F. (1991). “A generalized regression neural network.” IEEE Trans. Neural Netw., 2(6), 568–576.
Specht, D. F. (1996). Fuzzy logic and neural network handbook, McGraw-Hill, New York.
Stewart, J. P., Seed, R. B., and Fenves, G. L. (1998). “Empirical evaluation of inertial soil-structure interaction.” Rep. No. PEER-98/07, Pacific Earthquake Research Center, Univ. of California, Berkeley, Calif.
Stewart, J. P., and Stewart, A. F. (1997). “Analysis of soil-structure interaction effects on building response from earthquake strong motion recordings at 58 sites.” Rep. No. UCB/EERC-97/01, Earthquake Engineering Research Center, Univ. of California, Berkeley, Calif.
Ural, D., and Bayrak, B. (2006). “Liquefaction potential assessment in layered soils using neural networks.” Int'l J. Mech. Solids, 1(1), 1–17.
Ural, D., and Saka, H. (1998). “Liquefaction prediction by neural networks.” Elec. J. Geotech. Engrg., 3, 1–4.
Ural, D., Saygili, G., and Bayrak, B. (2003). “Liquefaction effects on housing during the Kocaeli, Turkey earthquake.” Int. J. Housing Sci. Applicat. 27(4), 269–285.
Wolf, J. P. (1988). Soil-structure interaction analysis in time domain, International Series in Civil Engineering and Engineering Mechanism, Prentice-Hall, Englewood Cliffs, N.J.
Information & Authors
Information
Published In
Journal of Urban Planning and Development
Volume 136 • Issue 2 • June 2010
Pages: 135 - 138
Copyright
© 2010 ASCE.
History
Received: Dec 5, 2006
Accepted: Mar 26, 2007
Published online: May 14, 2010
Published in print: Jun 2010
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.