Intelligent systems for engineers and scientists 3rd Edition by Adrian Hopgood ISBN 1439821208 978-1439821206
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Product details:
ISBN 10: 1439821208
ISBN 13: 978-1439821206
Author: Adrian A. Hopgood
The third edition of this bestseller examines the principles of artificial intelligence and their application to engineering and science, as well as techniques for developing intelligent systems to solve practical problems. Covering the full spectrum of intelligent systems techniques, it incorporates knowledge-based systems, computational intelligence, and their hybrids.
Using clear and concise language, Intelligent Systems for Engineers and Scientists, Third Edition features updates and improvements throughout all chapters. It includes expanded and separated chapters on genetic algorithms and single-candidate optimization techniques, while the chapter on neural networks now covers spiking networks and a range of recurrent networks. The book also provides extended coverage of fuzzy logic, including type-2 and fuzzy control systems. Example programs using rules and uncertainty are presented in an industry-standard format, so that you can run them yourself.
The first part of the book describes key techniques of artificial intelligence―including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), frames, objects, agents, symbolic learning, case-based reasoning, genetic algorithms, optimization algorithms, neural networks, hybrids, and the Lisp and Prolog languages. The second part describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control.
The author provides sufficient detail to help you develop your own intelligent systems for real applications. Whether you are building intelligent systems or you simply want to know more about them, this book provides you with detailed and up-to-date guidance.
Table of contents:
Chapter 1 Introduction
Chapter 2 Rule-Based Systems
Chapter 3 Handling Uncertainty: Probability and Fuzzy Logic
Chapter 4 Agents, Objects, and Frames
Chapter 5 Symbolic Learning
Chapter 6 Single-Candidate Optimization Algorithms
Chapter 7 Genetic Algorithms for Optimization
Chapter 8 Neural Networks
Chapter 9 Hybrid Systems
Chapter 10 Artificial Intelligence Programming Languages
Chapter 11 Systems for Interpretation and Diagnosis
Chapter 12 Systems for Design and Selection
Chapter 13 Systems for Planning
Chapter 14 Systems for Control
Chapter 15 The Future of Intelligent Systems
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