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Books > Computing & IT > Applications of computing > Artificial intelligence
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Dependability Modelling under Uncertainty - An Imprecise Probabilistic Approach (Paperback, Softcover reprint of hardcover 1st ed. 2008)
Loot Price: R2,653
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Dependability Modelling under Uncertainty - An Imprecise Probabilistic Approach (Paperback, Softcover reprint of hardcover 1st ed. 2008)
Series: Studies in Computational Intelligence, 148
Expected to ship within 18 - 22 working days
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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.
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