Fuzzy Logic Applications in Engineering Science / Edition 2

Fuzzy Logic Applications in Engineering Science / Edition 2

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by J. Harris
     
 

Fuzzy logic is a relatively new concept in science applications. Hitherto, fuzzy logic has been a conceptual process applied in the field of risk management. Its potential applicability is much wider than that, however, and its particular suitability for expanding our understanding of processes and information in science and engineering in our post-modern world is

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Overview

Fuzzy logic is a relatively new concept in science applications. Hitherto, fuzzy logic has been a conceptual process applied in the field of risk management. Its potential applicability is much wider than that, however, and its particular suitability for expanding our understanding of processes and information in science and engineering in our post-modern world is only just beginning to be appreciated.

Written as a companion text to the author’s earlier volume "An Introduction to Fuzzy Logic Applications", the book is aimed at professional engineers and students and those with an interest in exploring the potential of fuzzy logic as an information processing kit with a wide variety of practical applications in the field of engineering science and develops themes and topics introduced in the author’s earlier text.

Product Details

ISBN-13:
9789048170340
Publisher:
Springer Netherlands
Publication date:
11/23/2010
Series:
Intelligent Systems, Control and Automation: Science and Engineering Series, #29
Edition description:
Softcover reprint of hardcover 2nd ed. 2006
Pages:
226
Product dimensions:
6.14(w) x 9.21(h) x 0.51(d)

Meet the Author

Table of Contents

Comments and Definitions.- Fuzzy Geometry.- Material Selection.- Hydrodynamic Lubrication.- Elastohydrodynamic Lubrication.- Fatigue and Creep.- Cumulative Fatigue Damage Analysis.- Reliability Assessment.- Process Control.- Total Risk and Reliability with Human Factors.- On System Condition Auditing.- Reframing Standards Using Fuzzy Sets for Improved Quality Control.- On the Correlation of Statistical and Automatic Process Control.- Road Transport Fuzzy Logistics — A Case Study.

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