Structural Reliability Statistical Learning Perspectives /

This monograph presents an original approach to Structural Reliability from the perspective of Statistical Learning Theory. It proposes new methods for solving the reliability problem utilizing the recent developments in Computational Learning Theory, such as Neural Networks and Support Vector machi...

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Bibliographic Details
Main Author: Hurtado, Jorge Eduardo (Author, http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004.
Edition:1st ed. 2004.
Series:Lecture Notes in Applied and Computational Mechanics, 17
Subjects:
Online Access:Full Text via HEAL-Link
Description
Summary:This monograph presents an original approach to Structural Reliability from the perspective of Statistical Learning Theory. It proposes new methods for solving the reliability problem utilizing the recent developments in Computational Learning Theory, such as Neural Networks and Support Vector machines. It also demonstrates important issues on the management of samples in Monte Carlo simulation for structural reliability analysis purposes and examines the treatment of the structural reliability problem as a pattern recognition or classification task. This carefully written monograph is aiming at researchers and students in civil and mechanical engineering, especially in reliability engineering, structural analysis, or statistical learning.
Physical Description:XIV, 257 p. online resource.
ISBN:9783540409878
ISSN:1613-7736 ;
DOI:10.1007/978-3-540-40987-8