Authors:
- Explains how to generate an adequate description of uncertainty
- Shows how to justify semi-heuristic algorithms for processing uncertainty, and how to make these algorithms more computationally efficient
- Includes various examples and real-life cases
Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 15)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (5 chapters)
-
Front Matter
-
Back Matter
About this book
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.
Authors and Affiliations
-
Information Technology Department, El Paso Community College, El Paso, USA
Christian Servin
-
Department of Computer Science, University of Texas at El Paso, El Paso, USA
Vladik Kreinovich
Bibliographic Information
Book Title: Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion
Authors: Christian Servin, Vladik Kreinovich
Series Title: Studies in Systems, Decision and Control
DOI: https://doi.org/10.1007/978-3-319-12628-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2015
Hardcover ISBN: 978-3-319-12627-2Published: 03 December 2014
Softcover ISBN: 978-3-319-38587-7Published: 10 September 2016
eBook ISBN: 978-3-319-12628-9Published: 20 November 2014
Series ISSN: 2198-4182
Series E-ISSN: 2198-4190
Edition Number: 1
Number of Pages: VIII, 112
Number of Illustrations: 22 b/w illustrations
Topics: Computational Intelligence, Data Mining and Knowledge Discovery, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences