Intelligent Estimation: A Soft Computing Paradigm presents a unified treatment for a new paradigm of soft computing with AI-based approaches as applicable to system identification, parameter estimation, and filtering: Neuro-Fuzzy-GA Based System Identification, Parameter Estimation, and Filtering, known succinctly as Intelligent Estimation (IE). Offering a thorough understanding of soft computing-based estimation concepts and theory, the book discusses a modeling-control-system approach with numerous practical applications in solving mathematical modeling problems for industrial and aerospace engineering systems. It delves into theory, concepts and various ramifications of neural networks, fuzzy logic, and genetic algorithms for modeling, system identification, noise filtering, state estimation (including filtering), and parameter estimation. This book is intended for upper-level undergraduate and graduate engineering students studying soft computing, intelligent systems, and advanced control systems in industry applications. Instructors will be able to utilize a Solutions Manual and Figure Slides for their course.
