Data-driven Decision Making and Soft Computing

This book reflects the comprehensive exploration of the intersection between fuzzy decision-making and soft computing. It delves into the theoretical foundations of fuzzy decision-making and soft computing, exploring the underlying principles, algorithms, and mathematical frameworks. The text showcases the latest methodological advances in combining fuzzy decision-making with various soft computing techniques, such as neural networks, and evolutionary computation.

This book:
Provides a comprehensive coverage of data-driven decision-making techniques and soft computing methods. Aim at bridging the gap between theoretical concepts and practical implementation by offering real-world case studies, examples, and applications. Highlight emerging trends, recent advancements, and cutting-edge research in the field of data-driven decision-making and soft computing. Emphasize the real-world relevance of Fuzzy Decision Making and Soft Computing by showcasing practical applications across various domains. Showcases applications in domains such as control systems, pattern recognition, optimization, and decision support systems.
It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics, and communication engineering, computer science and engineering, and applied mathematics.