Fuzzy Logic And Neurofuzzy Applications Explained

Author : Constantin Von Altrock
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 376 pages
Book Rating : 4.11/5 ( download)

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Download or read book Fuzzy Logic and NeuroFuzzy Applications Explained written by Constantin Von Altrock and published by Prentice Hall. This book was released on 1995 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Disks contain simulation edition of fuzzyTECH development software from Inform Software corporation.

Author : Constantin Von Altrock
Publisher :
ISBN 13 : 9780133684650
Total Pages : 350 pages
Book Rating : 4.52/5 ( download)

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Download or read book Fuzzy Logic and NeuroFuzzy Applications Explained written by Constantin Von Altrock and published by . This book was released on 1995 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Peter Stavroulakis
Publisher : Springer Science & Business Media
ISBN 13 : 3642187625
Total Pages : 352 pages
Book Rating : 4.29/5 ( download)

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Download or read book Neuro-Fuzzy and Fuzzy-Neural Applications in Telecommunications written by Peter Stavroulakis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the first time, this highly interdisciplinary book covers the applications of neuro-fuzzy and fuzzy-neural scientific tools in a very wide area within the communications field. It deals with the important and modern areas of telecommunications amenable to such a treatment.

Author : Constantin Von Altrock
Publisher : Prentice Hall
ISBN 13 : 9780135915127
Total Pages : 0 pages
Book Rating : 4.20/5 ( download)

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Download or read book Fuzzy Logic and NeuroFuzzy Applications in Business and Finance written by Constantin Von Altrock and published by Prentice Hall. This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this hands-on, practical guide, you'll walk through powerful fuzzy logic business applications for business, including risk assessment, forecasting, supplier evaluation, customer targeting, and scheduling. You'll watch fuzzy logic at work analyzing credit risk, evaluating leases, making stock market decisions, and uncovering fraud.

Author : Horia-Nicolai L Teodorescu
Publisher : CRC Press
ISBN 13 : 1351364510
Total Pages : 479 pages
Book Rating : 4.15/5 ( download)

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Download or read book Fuzzy and Neuro-Fuzzy Systems in Medicine written by Horia-Nicolai L Teodorescu and published by CRC Press. This book was released on 2017-11-22 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy and Neuro-Fuzzy Systems in Medicineprovides a thorough review of state-of-the-art techniques and practices, defines and explains relevant problems, as well as provides solutions to these problems. After an introduction, the book progresses from one topic to another - with a linear development from fundamentals to applications.

Author : Mallick, Pradeep Kumar
Publisher : IGI Global
ISBN 13 : 1522557946
Total Pages : 300 pages
Book Rating : 4.44/5 ( download)

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Download or read book Emerging Trends and Applications in Cognitive Computing written by Mallick, Pradeep Kumar and published by IGI Global. This book was released on 2018-12-28 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Though an individual can process a limitless amount of information, the human brain can only comprehend a small amount of data at a time. Using technology can improve the process and comprehension of information, but the technology must learn to behave more like a human brain to employ concepts like memory, learning, visualization ability, and decision making. Emerging Trends and Applications in Cognitive Computing is a fundamental scholarly source that provides empirical studies and theoretical analysis to show how learning methods can solve important application problems throughout various industries and explain how machine learning research is conducted. Including innovative research on topics such as deep neural networks, cyber-physical systems, and pattern recognition, this collection of research will benefit individuals such as IT professionals, academicians, students, researchers, and managers.

Author : Rahul Kar
Publisher : John Wiley & Sons
ISBN 13 : 1394175116
Total Pages : 265 pages
Book Rating : 4.16/5 ( download)

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Download or read book Fuzzy Logic Applications in Computer Science and Mathematics written by Rahul Kar and published by John Wiley & Sons. This book was released on 2023-09-15 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: FUZZY LOGIC APPLICATIONS IN COMPUTER SCIENCE AND MATHEMATICSTICS The prime objective of developing this book is to provide meticulous details about the basic and advanced concepts of fuzzy logic and its all-around applications to different fields of mathematics and engineering. The basic steps of fuzzy inference systems starting from the core foundation of the fuzzy concepts are presented in this book. The fuzzy theory is a mathematical concept and, at the same time, it is applied to many versatile engineering fields and research domains related to computer science. The fuzzy system offers some knowledge about uncertainty and is also related to the theory of probability. A fuzzy logic-based model acts as the classifier for many different types of data belonging to several classes. Covered in this book are topics such as the fundamental concepts of mathematics, fuzzy logic concepts, probability and possibility theories, and evolutionary computing to some extent. The combined fields of neural network and fuzzy domain (known as the neuro-fuzzy system) are explained and elaborated. Each chapter has been produced in a very lucid manner, with grading from simple to complex to accommodate the anticipated different audiences. The application-oriented approach is the unique feature of this book. Audience This book will be read and used by a broad audience including applied mathematicians, computer scientists, and industry engineers.

Author : Himanshu Singh
Publisher : Apress
ISBN 13 : 1484253612
Total Pages : 270 pages
Book Rating : 4.18/5 ( download)

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Download or read book Deep Neuro-Fuzzy Systems with Python written by Himanshu Singh and published by Apress. This book was released on 2019-11-30 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain insight into fuzzy logic and neural networks, and how the integration between the two models makes intelligent systems in the current world. This book simplifies the implementation of fuzzy logic and neural network concepts using Python. You’ll start by walking through the basics of fuzzy sets and relations, and how each member of the set has its own membership function values. You’ll also look at different architectures and models that have been developed, and how rules and reasoning have been defined to make the architectures possible. The book then provides a closer look at neural networks and related architectures, focusing on the various issues neural networks may encounter during training, and how different optimization methods can help you resolve them. In the last section of the book you’ll examine the integrations of fuzzy logics and neural networks, the adaptive neuro fuzzy Inference systems, and various approximations related to the same. You’ll review different types of deep neuro fuzzy classifiers, fuzzy neurons, and the adaptive learning capability of the neural networks. The book concludes by reviewing advanced neuro fuzzy models and applications. What You’ll Learn Understand fuzzy logic, membership functions, fuzzy relations, and fuzzy inferenceReview neural networks, back propagation, and optimizationWork with different architectures such as Takagi-Sugeno model, Hybrid model, genetic algorithms, and approximations Apply Python implementations of deep neuro fuzzy system Who This book Is For Data scientists and software engineers with a basic understanding of Machine Learning who want to expand into the hybrid applications of deep learning and fuzzy logic.

Author : Jenny Carter
Publisher : Springer Nature
ISBN 13 : 3030664740
Total Pages : 269 pages
Book Rating : 4.49/5 ( download)

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Download or read book Fuzzy Logic written by Jenny Carter and published by Springer Nature. This book was released on 2021-05-04 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its inception, fuzzy logic has attracted an incredible amount of interest, and this interest continues to grow at an exponential rate. As such, scientists, researchers, educators and practitioners of fuzzy logic continue to expand on the applicability of what and how fuzzy can be utilised in the real-world. In this book, the authors present key application areas where fuzzy has had significant success. The chapters cover a plethora of application domains, proving credence to the versatility and robustness of a fuzzy approach. A better understanding of fuzzy will ultimately allow for a better appreciation of fuzzy. This book provides the reader with a varied range of examples to illustrate what fuzzy logic can be capable of and how it can be applied. The text will be ideal for individuals new to the notion of fuzzy, as well as for early career academics who wish to further expand on their knowledge of fuzzy applications. The book is also suitable as a supporting text for advanced undergraduate and graduate-level modules on fuzzy logic, soft computing, and applications of AI.

Author : Robert Fuller
Publisher : Springer Science & Business Media
ISBN 13 : 3790818526
Total Pages : 300 pages
Book Rating : 4.29/5 ( download)

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Download or read book Introduction to Neuro-Fuzzy Systems written by Robert Fuller and published by Springer Science & Business Media. This book was released on 2013-06-05 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy sets were introduced by Zadeh (1965) as a means of representing and manipulating data that was not precise, but rather fuzzy. Fuzzy logic pro vides an inference morphology that enables approximate human reasoning capabilities to be applied to knowledge-based systems. The theory of fuzzy logic provides a mathematical strength to capture the uncertainties associ ated with human cognitive processes, such as thinking and reasoning. The conventional approaches to knowledge representation lack the means for rep resentating the meaning of fuzzy concepts. As a consequence, the approaches based on first order logic and classical probablity theory do not provide an appropriate conceptual framework for dealing with the representation of com monsense knowledge, since such knowledge is by its nature both lexically imprecise and noncategorical. The developement of fuzzy logic was motivated in large measure by the need for a conceptual framework which can address the issue of uncertainty and lexical imprecision. Some of the essential characteristics of fuzzy logic relate to the following [242]. • In fuzzy logic, exact reasoning is viewed as a limiting case of ap proximate reasoning. • In fuzzy logic, everything is a matter of degree. • In fuzzy logic, knowledge is interpreted a collection of elastic or, equivalently, fuzzy constraint on a collection of variables. • Inference is viewed as a process of propagation of elastic con straints. • Any logical system can be fuzzified. There are two main characteristics of fuzzy systems that give them better performance für specific applications.