Uncertainty Modeling and Analysis in Engineering and the Sciences

1. Auflage 2006
ISBN: 978-1-58488-644-0
Verlag: CRC Press

Buch, Englisch, 400 Seiten, Format (B × H): 162 mm x 235 mm, Gewicht: 685 g

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.

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.

The book introduces fundamental concepts of classical, fuzzy, and rough sets, probability, Bayesian methods, interval analysis, fuzzy arithmetic, interval probabilities, evidence theory, open-world models, sequences, and possibility theory. The authors present these methods to meet the needs of practitioners in many fields, emphasizing the practical use, limitations, advantages, and disadvantages of the methods.

Zielgruppe

Professional

Autoren/Hrsg.

Ayyub, Bilal M

Klir, George J

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik

Inhaltsverzeichnis

Systems, knowledge, and ignorance. Encoding data and expressing information. Uncertainty and information synthesis. Uncertainty measures. Uncertainty-based principles and knowledge construction. Uncertainty propagation for systems. Expert opinions and elicitation methods. Visualization of uncertainty. Historical Perspectives on Knowledge.

Über Autor(innen)

Bilal M. Ayyub, George J. Klir