Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion (Hardcover, 2015 ed.)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Systems, Decision and Control, 15
Release date:	November 2014
First published:	2015
Authors:	Christian Servin • Vladik Kreinovich
Dimensions:	235 x 155 x 8mm (L x W x T)
Format:	Hardcover
Pages:	112
Edition:	2015 ed.
ISBN-13:	978-3-319-12627-2
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-319-12627-X
Barcode:	9783319126272

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