This book identifies the important uncertainties to use in real-world problem modeling. Having information about several types of ambiguities, vagueness, and uncertainties is vital in modeling problems that involve linguistic variables, parameters, and word computing. Today, since most of our real-world problems are related to decision-making at the right time, we need to apply intelligent decision science. Clearly, in order to have an appropriate and flexible mathematical model, every intelligent system requires real data on our environment. Presenting problems that can be represented using mathematical models to create a system of linear equations, this book discusses the latest insights into uncertain information.
"The book is well organized and presents the most important notions of uncertain information and linear systems. The book is suitable for senior undergraduate students as well as practical engineers, scientist and researchers interested in uncertain information and linear systems." (Seenith Sivasundaram, zbMATH 1431.93002, 2020)