Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion by Christian ServinPropagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion by Christian Servin

Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data…

byChristian Servin, Vladik Kreinovich

Hardcover | December 3, 2014

Pricing and Purchase Info

$206.95

Earn 1,035 plum® points

Prices and offers may vary in store

Quantity:

In stock online

Ships free on orders over $25

Not available in stores

about

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.

Title:Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data…Format:HardcoverDimensions:112 pagesPublished:December 3, 2014Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:331912627X

ISBN - 13:9783319126272

Look for similar items by category:

Reviews

Table of Contents

Introduction.- Towards a More Adequate Description of Uncertainty.- Towards Justification of Heuristic Techniques for Processing Uncertainty.- Towards More Computationally Efficient Techniques for Processing Uncertainty.- Towards Better Ways of Extracting Information About Uncertainty from Data.