Synonyms
Overview of Uncertainty in Earthquake Engineering; Uncertainty in Earthquake Engineering Background; Uncertainty in Earthquake Engineering Introduction; Uncertainty in Earthquake Engineering Overview
Introduction
Uncertainty is associated with many aspects of earthquake engineering. Considerable uncertainty resides in the prediction of earthquake occurrence, prediction of seismic forces, estimated capacity of a structural system to withstand such forces, and consequences associated with seismic events. This challenging problem lends itself to information/partial knowledge and uncertainty in many forms.
Traditionally, probabilistic methods have often been employed to systematically treat the inherent uncertainty in earthquake engineering applications. Notably, probability theory is used in seismic hazard analysis first outlined by Cornell (1968). Probabilistic methods also underlie load and resistance criteria for structural design. A probabilistic design methodology is based...
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References
Ang AH-S, Tang WH (2007) Probability concepts in engineering emphasis on applications to civil and environmental engineering, 2nd edn. Wiley, Hoboken
Applied Technology Council (1985) Earthquake damage evaluation data for California (ATC 13). Applied Technology Council (ATC), Redwood City
Benjamin JR, Cornell CA (1970) Probability, statistics, and decision for civil engineers. McGraw-Hill, New York
Cornell AC (1968) Engineering seismic risk analysis. Bull Seismol Soc Am 58(5):1583–1606
Cornell AC (1969) A probability-based structural code. ACI J 66:974–985
Cornell AC, Krawinkler H (2000) Progress and challenges in seismic performance assessment. PEER Center News, vol 3, no. 2
Dempster AP (1967) Upper and lower probabilities induced by a multivalued mapping. Ann Math Stat 38(2):325–359
Dubois D, Prade H (1988) Possibility theory: an approach to computerized processing of uncertainty. Plenum, New York
Ellingwood BR, Galambos TV, MacGregor JG, Cornell CA (1980) Development of a probability based load criterion for American National Standard A58. National Bureau of Standards, U.S. Department of Commerce, Washington, DC
Federal Emergency Management Agency (FEMA) (1997) FEMA 273, NEHRP guidelines for the seismic rehabilitation of buildings. Federal Emergency Management Agency, Washington, DC
Federal Emergency Management Agency (FEMA) (2000) FEMA 356, prestandard and commentary for the seismic rehabilitation of buildings. Federal Emergency Management Agency, Washington, DC
Hacking I (2006) The emergence of probability: a philosophical study of early ideas about probability intuition and statistical inference, Secondth edn. Cambridge University Press, Cambridge, UK
Klir GJ (2006) Uncertainty and information foundations of generalized information theory. Wiley, Hoboken
Klir GJ, Smith RM (2001) On measuring uncertainty and uncertainty-based information: recent developments. Ann Math Artif Intell 32(1–4):5–33
Klir GJ, Yuan B (1995) Fuzzy sets and fuzzy logic theory and applications. Prentice Hall, Upper Saddle River
National Institute of Building Sciences (1997) HAZUS earthquake loss estimation methodology. NIBS Document No. 5201. Federal Emergency Management Agency. Washington, DC
Porter K (2003) An overview of PEER’s performance-based earthquake engineering methodology. Ninth international conference of applications of statistics and probability in civil engineering (ICASP9), San Francisco, 6–9 July 2003
Ravindra MK, Galambos TV (1978) Load and resistance factor design for steel. J Struct Div Am Soc Civil Eng (ASCE) 104:1337––1353
Ross TJ (2010) Fuzzy logic with engineering applications, 3rd edn. Wiley, West Sussex
Shafer G (1976) A mathematical theory of evidence. Princeton University Press, Princeton
Shafer G (1987) Belief functions and possibility measures. In: Bezdek JC (ed) Analysis of fuzzy information, vol 1, Mathematics and logic. CRC Press, Boca Raton
Shafer G (2012) A mathematical theory of evidence. Glenn Shafer, http://www.glennshafer.com/books/amte.html. 7 Nov 2012
Smets P (1994) What is Dempster-Shafer’s model? Advances in the Dempster-Shafer theory of evidence. Wiley, New York, pp 5–34
Vick SG (2002) Degrees of belief subjective probability and engineering judgment. American Society of Civil Engineers (ASCE) Press, Reston
Whitman RV (1973) Damage probability matrices for prototype buildings, Massachusetts Institute of Technology Department of Civil Engineering, Research Report R73–57. MIT Press, Cambridge, MA
Whitman RV, Hong S, Reed JW (1973) Damage Statistics for High-Rise Buildings in the Vicinity of the San Fernando Earthquake, Massachusetts Institute of Technology Department of Civil Engineering, Research Report R73–24. MIT Press, Cambridge, MA
Yager RR, Liu L (2008) In: Kacprzyk J (ed) 1 Classic Works of the Dempster-Shafer Theory of Belief Functions: An Introduction, vol 219, Studies in fuzziness and soft computing. Springer, New York
Zadeh LA (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Set Syst 1:3–28
Zadeh LA (1986) A simple view of the Dempster-Shafer theory of evidence and its implication for the rule of combination. AI Mag 7(2):85–90
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Elwood, E., Corotis, R. (2015). Uncertainty Theories: Overview. In: Beer, M., Kougioumtzoglou, I.A., Patelli, E., Au, SK. (eds) Encyclopedia of Earthquake Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35344-4_164
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DOI: https://doi.org/10.1007/978-3-642-35344-4_164
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