Overview
- Latest research in Dependability modelling under Uncertainty with applications to mechatronics
Part of the book series: Studies in Computational Intelligence (SCI, volume 148)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Mechatronic design processes have become shorter and more parallelized, induced by growing time-to-market pressure. Methods that enable quantitative analysis in early design stages are required, should dependability analyses aim to influence the design. Due to the limited amount of data in this phase, the level of uncertainty is high and explicit modeling of these uncertainties becomes necessary.
This work introduces new uncertainty-preserving dependability methods for early design stages. These include the propagation of uncertainty through dependability models, the activation of data from similar components for analyses and the integration of uncertain dependability predictions into an optimization framework. It is shown that Dempster-Shafer theory can be an alternative to probability theory in early design stage dependability predictions. Expert estimates can be represented, input uncertainty is propagated through the system and prediction uncertainty can be measured and interpreted. The resulting coherent methodology can be applied to represent the uncertainty in dependability models.
Bibliographic Information
Book Title: Dependability Modelling under Uncertainty
Book Subtitle: An Imprecise Probabilistic Approach
Authors: Philipp Limbourg
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-69287-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Hardcover ISBN: 978-3-540-69286-7Published: 20 August 2008
Softcover ISBN: 978-3-642-08880-3Published: 18 November 2010
eBook ISBN: 978-3-540-69287-4Published: 08 September 2008
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVI, 140
Number of Illustrations: 68 b/w illustrations
Topics: Theory of Computation, Mathematical and Computational Engineering, Artificial Intelligence