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Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion (Studies in Systems, Decision and Control, 15) - Hardcover
Synopsis
On various examples ranging from geosciences to environmental sciences, this
book explains how to generate an adequate description of uncertainty, how to justify
semiheuristic algorithms for processing uncertainty, and how to make these algorithms
more computationally efficient. It explains in what sense the existing approach to
uncertainty as a combination of random and systematic components is only an
approximation, presents a more adequate three-component model with an additional
periodic error component, and explains how uncertainty propagation techniques can
be extended to this model. The book provides a justification for a practically efficient
heuristic technique (based on fuzzy decision-making). It explains how the computational
complexity of uncertainty processing can be reduced. The book also shows how to
take into account that in real life, the information about uncertainty is often only
partially known, and, on several practical examples, explains how to extract the missing
information about uncertainty from the available data.
"synopsis" may belong to another edition of this title.
From the Back Cover
On various examples ranging from geosciences to environmental sciences, this
book explains how to generate an adequate description of uncertainty, how to justify
semiheuristic algorithms for processing uncertainty, and how to make these algorithms
more computationally efficient. It explains in what sense the existing approach to
uncertainty as a combination of random and systematic components is only an
approximation, presents a more adequate three-component model with an additional
periodic error component, and explains how uncertainty propagation techniques can
be extended to this model. The book provides a justification for a practically efficient
heuristic technique (based on fuzzy decision-making). It explains how the computational
complexity of uncertainty processing can be reduced. The book also shows how to
take into account that in real life, the information about uncertainty is often only
partially known, and, on several practical examples, explains how to extract the missing
information about uncertainty from the available data.
"About this title" may belong to another edition of this title.
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Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion.
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Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion (Studies in Systems, Decision and Control, 15)
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Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion
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Springer International Publishing, 2014
ISBN 10: 331912627X
ISBN 13: 9783319126272
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Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion (Studies in Systems, Decision and Control, 15)
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Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion
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Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion
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Springer International Publishing Dez 2014, 2014
ISBN 10: 331912627X
ISBN 13: 9783319126272
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -On various examples ranging from geosciences to environmental sciences, thisbook explains how to generate an adequate description of uncertainty, how to justifysemiheuristic algorithms for processing uncertainty, and how to make these algorithmsmore computationally efficient. It explains in what sense the existing approach touncertainty as a combination of random and systematic components is only anapproximation, presents a more adequate three-component model with an additionalperiodic error component, and explains how uncertainty propagation techniques canbe extended to this model. The book provides a justification for a practically efficientheuristic technique (based on fuzzy decision-making). It explains how the computationalcomplexity of uncertainty processing can be reduced. The book also shows how totake into account that in real life, the information about uncertainty is often onlypartially known, and, on several practical examples, explains how to extract the missinginformation about uncertainty from the available data. 120 pp. Englisch. Seller Inventory # 9783319126272
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Propagation of Interval and Probabilistic Uncertainty in.
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Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion
Published by
Springer International Publishing, 2014
ISBN 10: 331912627X
ISBN 13: 9783319126272
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Hardcover
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explains how to generate an adequate description of uncertaintyShows how to justify semi-heuristic algorithms for processing uncertainty, and how to make these algorithms more computationally efficientIncludes various examples and real-life. Seller Inventory # 4499297
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Propagation of Interval and Probabilistic Uncertainty in.
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