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Business & Management - Operations Research & Decision Theory | Applied Research in Uncertainty Modeling and Analysis

Applied Research in Uncertainty Modeling and Analysis

Ayyub, Bilal (Ed.)

2005, XVI, 545 p.

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

In this fascinating overview of the field, the authors provide broad coverage of uncertainty analysis/modeling and its application. Applied Research in Uncertainty Modeling and Analysis presents the perspectives of various researchers and practitioners on uncertainty analysis and modeling outside their own fields and domain expertise. Rather than focusing explicitly on theory, the authors use real-world examples to demonstrate the strength of the chosen methodology.

Applied Research in Uncertainty Modeling and Analysis concentrates on general aspects of uncertainty, modeling, and methods, and focuses on various applications, included Biomedical Engineering, Chemical Engineering, Structural Engineering, and Transportation Engineering.

Content Level » Research

Keywords » Analysis - automation - fuzzy - model - modeling - ontology - simulation

Related subjects » Economic Theory - Engineering - Operations Research & Decision Theory

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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