Harish Garg

This book explains the foundational principles of fuzzy algebra, including fuzzy sets, fuzzy operations, and fuzzy relations. It shows how fuzzy algebra can be applied in artificial intelligence, particularly in areas such as decision-making, pattern recognition, and machine learning, where uncertainty and imprecision are common. It demonstrates the use of fuzzy algebra in engineering disciplines, such as control systems, cybersecurity, signal processing, and robotics, where fuzzy logic can be used to model and solve complex and real-world problems. This makes the book valuable not just for process engineers, but also for researchers in multiple domains. This book is designed to familiarize data science, machine learning and other engineering professionals, in a relatively simple and easy to understand fashion, with decision making skills founded on calculations and case study based quantitative analysis.

This book offers a comprehensive review of the different types of fuzzy sets that have been developed in the last few years. Each chapter is dedicated to a type of fuzzy set, which is at first introduced and described in detail, together with its properties. In turn, its application in an optimization and/or decision-making problem is discussed. In particular, the book highlights current research gaps and future research directions on fuzzy numbers in decision analysis and transportation problems. It is intended as a self-contained reference guide for scientists and engineers interested in applying fuzzy set theory for solving optimization problems.