"Uncertainty Modeling and Analysis in Engineering and the Sciences" by Bilal M. Ayyub, George J. Klir

This volume covers primary components of ignorance and their impact on practice and decision making. It provides an overview of the current state of uncertainty modeling and analysis, and reviews emerging theories while emphasizing practical applications in science and engineering.

Engineers and scientists often need to solve complex problems with incomplete information resources, necessitating a proper treatment of uncertainty and a reliance on expert opinions. Uncertainty Modeling and Analysis in Engineering and the Sciences prepares current and future analysts and practitioners to understand the fundamentals of knowledge and ignorance, how to model and analyze uncertainty, and how to select appropriate analytical tools for particular problems.

Features
-Provides a systems framework for the analysis and modeling of uncertainty
-Summarizes methods for encoding data and expressing information
-Illustrates methods for uncertainty and information synthesis
-Develops methods for uncertainty measures and related criteria for knowledge construction
-Examines methods for uncertainty propagation in input-output systems
-Describes methods for visualizing uncertainty
-Explains how to elicit opinions of experts in order to increase the truthfulness of outcomes
-Contains computational examples, detailed engineering applications, and exercise problems related to chapter materials