Uncertainty Modeling and Analysis in Engineering and the Sciences

Book Details:

• Book Title: Uncertainty Modeling and Analysis in Engineering and the Sciences

• Author: Bilal M. Ayyub

• Publisher: CRC Press

• Language: English

• Edition: 1st Edition

• ISBN: 9781584886440

• Pages: 400

• Cover: Hardcover

• Dimensions: 9.3 x 6.2 x 1.1 inches

About the Book:

Uncertainty Modeling and Analysis in Engineering and the Sciences by Bilal M. Ayyub is a comprehensive guide that addresses the fundamental principles of handling uncertainty in engineering and scientific analysis. Engineers and scientists often face complex problems where information is incomplete or uncertain, making it essential to understand how to model and analyze uncertainty effectively. This book provides a deep dive into uncertainty modeling, covering a wide range of techniques and methodologies for handling different types of uncertainty in various applications.

The book starts by exploring the concept of ignorance and its impact on practical decision-making and analysis. It then provides a broad overview of the current state of uncertainty modeling, presenting both classical and emerging theories. Key methods introduced include fuzzy and rough sets, probability theory, Bayesian methods, interval analysis, fuzzy arithmetic, evidence theory, and possibility theory. Each technique is discussed with an emphasis on its practical applications, limitations, advantages, and disadvantages, making it an essential resource for both current and future analysts and practitioners.

The volume is designed for engineers, scientists, and decision-makers who need to incorporate uncertainty into their models. It offers a clear understanding of how to choose the most appropriate analytical tools for specific problems, making it a valuable reference for professionals in various fields where uncertainty plays a significant role. Whether you are dealing with incomplete data, expert opinions, or complex systems, this book provides a detailed and practical framework for making informed decisions in uncertain environments.