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Applied Research in Uncertainty Modeling and Analysis / Edition 1
     

Applied Research in Uncertainty Modeling and Analysis / Edition 1

by Bilal Ayyub, Bilal M. Ayyub
 

ISBN-10: 0387235353

ISBN-13: 9780387235356

Pub. Date: 02/01/2005

Publisher: Springer US

Uncertainty has been a concern to engineers, managers, and scientists for many years in engineering and sciences. Uncertainty has for a long time been considered synonymous with random, shastic, statistic, or probabilistic. Since the early sixties views on uncertainty have become more heterogeneous and more tools that model uncertainty than statistics have been

Overview

Uncertainty has been a concern to engineers, managers, and scientists for many years in engineering and sciences. Uncertainty has for a long time been considered synonymous with random, shastic, statistic, or probabilistic. Since the early sixties views on uncertainty have become more heterogeneous and more tools that model uncertainty than statistics have been proposed by several engineers and scientists. The tool/ method to model uncertainty in a specific context should really be choices by considering the features of the phenomenon under consideration not independently of what is known about the system and what causes uncertainty.

Applied Research in Uncertainty Modeling Analysis concentrates on general aspects of uncertainty, modeling, and methods, and consists of large numbers of examples on engineering and sciences.

Product Details

ISBN-13:
9780387235356
Publisher:
Springer US
Publication date:
02/01/2005
Series:
International Series in Intelligent Technologies , #20
Edition description:
2005
Pages:
545
Product dimensions:
6.10(w) x 9.25(h) x 0.05(d)

Table of Contents

Self-Organizing Neural Networks by Dynamic and Spatial Changing Weights.- Uncertainty in the Automation of Ontology Matching.- Uncertainty Modeling of Data and Uncertainty Propagation for Risk Studies.- Development of Quadratic Neural Unit with Applications to Pattern Classification.- Quadratic and Cubic Neural Units for Identification and Fast State Feedback Control of Unknown Non-Linear Dynamic Systems.- Crisp Simulation of Fuzzy Computations.- Exploratory Modeling Managing Uncertain Risk.- Multi-Interval Elicitation of Random Intervals for Engineering Reliability Analysis.- Biological Applications.- Engineering and Sciences.- Transportation Engineering.- Structural Engineering.

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