Intelligent Estimation A Soft Computing Paradigm | 35.33 MB
Title: Intelligent Estimation A Soft Computing Paradigm
Author: Raol, Jitendra R., George, Sara M.
Category: Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing, Science & Nature, Technology
Language: English | 331 Pages | ISBN: 9781040675359
Description:
Intelligent Estimation: A Soft Computing Paradigm presents a unified treatment of a new soft computing framework using AI-based approaches for system identification, parameter estimation, and filtering. This Neuro-Fuzzy-GA-based methodology, succinctly referred to as Intelligent Estimation (IE), integrates these estimation and filtering tasks within a single paradigm.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, filtering, and 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.
Intelligent Estimation: A Soft Computing Paradigm presents a unified treatment of a new soft computing framework using AI-based approaches for system identification, parameter estimation, and filtering. This Neuro-Fuzzy-GA-based methodology, succinctly referred to as Intelligent Estimation (IE), integrates these estimation and filtering tasks within a single paradigm.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, filtering, and 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.
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