Fuzzy Logic and Intelligent Systems

Softcover Nachdruck of the original 1. Auflage 1995
ISBN: 978-94-017-3773-9
Verlag: Springer Netherlands

Buch, Englisch, Band 3, 450 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 703 g

Reihe: International Series in Intelligent Technologies

One of the attractions of fuzzy logic is its utility in solving many real engineering problems. As many have realised, the major obstacles in building a real intelligent machine involve dealing with random disturbances, processing large amounts of imprecise data, interacting with a dynamically changing environment, and coping with uncertainty. Neural-fuzzy techniques help one to solve many of these problems.
Fuzzy Logic and Intelligent Systems reflects the most recent developments in neural networks and fuzzy logic, and their application in intelligent systems. In addition, the balance between theoretical work and applications makes the book suitable for both researchers and engineers, as well as for graduate students.

Zielgruppe

Research

Autoren/Hrsg.

Gupta, Madan M.

Fachgebiete

• Mathematik | Informatik Mathematik Mathematik Allgemein Grundlagen der Mathematik
• Mathematik | Informatik Mathematik Mathematik Allgemein Mathematische Logik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung

Inhaltsverzeichnis

Improvement of Fuzzy Control Methods.- Neural Networks and Fuzzy Basis Functions for Functional Approximation.- Ordering Fuzzy Real Quantities.- Fuzzy Logic Controllers for Aircraft Flight Control.- A Classical Controller: A Special Case of The Fuzzy Logic Controller.- Real Time Fuzzy Logic Controller for Balancing a Beam-and-Ball System.- Design of Fuzzy Controllers Based on Frequency And Transient Characteristics.- Fuzzy Inference Integrating 3D Measuring System with Adaptive Sensing Strategy.- Robot Hand-Eye Coordination Based on Fuzzy Logic.- Using FPGA Technique for Design and Implementation of a fuzzy Inference System.- An Empirical Analysis of One Type of Direct Adaptive Fuzzy Control.- Automatic Optimal Design of Fuzzy Systems Based on Universal Approximation and Evolutionary Programming.- Intelligent Control Using Dynamic Neural Networks with Robotic Applications.- Camcorder Operation Judgement Using a Neural Computing Approach.- Model Reduction and Control of Multistage Flash (MSF) Desalinization Plants.