New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics

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Publisher : Springer Nature
ISBN 13 : 3031556844
Total Pages : 422 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics by : Oscar Castillo

Download or read book New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics written by Oscar Castillo and published by Springer Nature. This book was released on with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications

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Author :
Publisher : Springer
ISBN 13 : 3319710087
Total Pages : 546 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications by : Oscar Castillo

Download or read book Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications written by Oscar Castillo and published by Springer. This book was released on 2018-01-10 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises papers on diverse aspects of fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics and their application in various areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book is organized into seven main parts, each with a collection of papers on a similar subject. The first part presents new concepts and algorithms based on type-2 fuzzy logic for dynamic parameter adaptation in meta-heuristics. The second part discusses network theory and applications, and includes papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The third part addresses the theory and practice of meta-heuristics in different areas of application, while the fourth part describes diverse fuzzy logic applications in the control area, which can be considered as intelligent controllers. The next two parts explore applications in areas, such as time series prediction, and pattern recognition and new optimization and evolutionary algorithms and their applications respectively. Lastly, the seventh part addresses the design and application of different hybrid intelligent systems.

New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics

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Publisher : Springer Nature
ISBN 13 : 3031082664
Total Pages : 471 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics by : Oscar Castillo

Download or read book New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics written by Oscar Castillo and published by Springer Nature. This book was released on 2022-09-30 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are applied to areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.

Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications

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Publisher : Springer Nature
ISBN 13 : 3030687767
Total Pages : 383 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications by : Oscar Castillo

Download or read book Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications written by Oscar Castillo and published by Springer Nature. This book was released on 2021-03-24 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: We describe in this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their application in areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that presents theory and practice of meta-heuristics in different areas of application. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical applications. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems.

Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics

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Publisher : Springer Nature
ISBN 13 : 3031289994
Total Pages : 489 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics by : Oscar Castillo

Download or read book Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics written by Oscar Castillo and published by Springer Nature. This book was released on 2023-06-12 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, recent theoretical developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are presented in application areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, decision-making, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are a group of papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also a group of papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers outlines diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different application areas. In addition, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas. Finally, there are a group of papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.

New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms

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Publisher : Springer Nature
ISBN 13 : 3031537130
Total Pages : 204 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms by : Patricia Melin

Download or read book New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms written by Patricia Melin and published by Springer Nature. This book was released on with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design

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Author :
Publisher : Springer Nature
ISBN 13 : 3031220420
Total Pages : 254 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design by : Oscar Castillo

Download or read book Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design written by Oscar Castillo and published by Springer Nature. This book was released on 2023-01-27 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations. In addition, the above-mentioned methods are applied to areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. Nowadays, the main topic of the book is highly relevant, as most current intelligent systems and devices in use utilize some form of intelligent feature to enhance their performance. In addition, on the theoretical side, new and advanced models and algorithms of type-2 and type-3 fuzzy logic are presented, which are of great interest to researchers working on these areas. Also, new nature-inspired optimization algorithms and innovative neural models are put forward in the manuscript, which are very popular subjects, at this moment. There are contributions on theoretical aspects as well as applications, which make the book very appealing to a wide audience, ranging from researchers to professors and graduate students.

Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications

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Author :
Publisher : Springer Nature
ISBN 13 : 3030354458
Total Pages : 792 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications by : Oscar Castillo

Download or read book Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications written by Oscar Castillo and published by Springer Nature. This book was released on 2020-02-27 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the latest advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid intelligent combinations, and their applications in the areas such as intelligent control, robotics, pattern recognition, medical diagnosis, time series prediction, and optimization. The topic is highly relevant as most current intelligent systems and devices use some form of intelligent feature to enhance their performance. The book also presents new and advanced models and algorithms of type-2 fuzzy logic and intuitionistic fuzzy systems, which are of great interest to researchers in these areas. Further, it proposes novel, nature-inspired optimization algorithms and innovative neural models. Featuring contributions on theoretical aspects as well as applications, the book appeals to a wide audience.

Metaheuristic Procedures for Training Neural Networks

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Publisher : Springer Science & Business Media
ISBN 13 : 0387334165
Total Pages : 258 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Metaheuristic Procedures for Training Neural Networks by : Enrique Alba

Download or read book Metaheuristic Procedures for Training Neural Networks written by Enrique Alba and published by Springer Science & Business Media. This book was released on 2006-08-25 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides successful implementations of metaheuristic methods for neural network training. It is the first book to achieve this objective. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own. Overall, the book's aim is to provide a broad coverage of the concepts, methods, and tools of the important area of ANNs within the realm of continuous optimization.

Fuzzy Neural Network Theory and Application

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Author :
Publisher : World Scientific
ISBN 13 : 9789812794215
Total Pages : 400 pages
Book Rating : 4.7/5 (942 download)

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Book Synopsis Fuzzy Neural Network Theory and Application by : Puyin Liu

Download or read book Fuzzy Neural Network Theory and Application written by Puyin Liu and published by World Scientific. This book was released on 2004 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to help the reader grasp the underlying theory. This is a valuable reference for scientists and engineers working in mathematics, computer science, control or other fields related to information processing. It can also be used as a textbook for graduate courses in applied mathematics, computer science, automatic control and electrical engineering. Contents: Fuzzy Neural Networks for Storing and Classifying; Fuzzy Associative Memory OCo Feedback Networks; Regular Fuzzy Neural Networks; Polygonal Fuzzy Neural Networks; Approximation Analysis of Fuzzy Systems; Stochastic Fuzzy Systems and Approximations; Application of FNN to Image Restoration. Readership: Scientists, engineers and graduate students in applied mathematics, computer science, automatic control and information processing."

Fuzzy and Neural: Interactions and Applications

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Publisher : Physica
ISBN 13 : 379081881X
Total Pages : 161 pages
Book Rating : 4.7/5 (98 download)

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Book Synopsis Fuzzy and Neural: Interactions and Applications by : James J. Buckley

Download or read book Fuzzy and Neural: Interactions and Applications written by James J. Buckley and published by Physica. This book was released on 2013-06-05 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary purpose of this book is to present information about selected topics on the interactions and applications of fuzzy + neural. Most of the discussion centers around our own research in these areas. Fuzzy + neural can mean many things: (1) approximations between fuzzy systems and neu ral nets (Chapter 4); (2) building hybrid neural nets to equal fuzzy systems (Chapter 5); (3) using neura.l nets to solve fuzzy problems (Chapter 6); (4) approximations between fuzzy neural nets and other fuzzy systems (Chap ter 8); (5) constructing hybrid fuzzy neural nets for certain fuzzy systems (Chapters 9, 10); or (6) computing with words (Chapter 11). This book is not intend to be used primarily as a text book for a course in fuzzy + neural because we have not included problems at the end of each chapter, we have omitted most proofs (given in the references), and we have given very few references. We wanted to keep the mathematical prerequisites to a minimum so all longer, involved, proofs were omitted. Elementary dif ferential calculus is the only prerequisite needed since we do mention partial derivatives once or twice.

NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM

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Publisher : PHI Learning Pvt. Ltd.
ISBN 13 : 8120321863
Total Pages : 459 pages
Book Rating : 4.1/5 (23 download)

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Book Synopsis NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM by : S. RAJASEKARAN

Download or read book NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM written by S. RAJASEKARAN and published by PHI Learning Pvt. Ltd.. This book was released on 2003-01-01 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence. The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as neuro-fuzzy, fuzzy-genetic, and neuro-genetic systems. The hybridization of the technologies is demonstrated on architectures such as Fuzzy-Back-propagation Networks (NN-FL), Simplified Fuzzy ARTMAP (NN-FL), and Fuzzy Associative Memories. The book also gives an exhaustive discussion of FL-GA hybridization. Every architecture has been discussed in detail through illustrative examples and applications. The algorithms have been presented in pseudo-code with a step-by-step illustration of the same in problems. The applications, demonstrative of the potential of the architectures, have been chosen from diverse disciplines of science and engineering. This book with a wealth of information that is clearly presented and illustrated by many examples and applications is designed for use as a text for courses in soft computing at both the senior undergraduate and first-year post-graduate engineering levels. It should also be of interest to researchers and technologists desirous of applying soft computing technologies to their respective fields of work.

Type-2 Fuzzy Logic: Theory and Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 3540762833
Total Pages : 252 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Type-2 Fuzzy Logic: Theory and Applications by : Oscar Castillo

Download or read book Type-2 Fuzzy Logic: Theory and Applications written by Oscar Castillo and published by Springer Science & Business Media. This book was released on 2008-02-20 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes new methods for building intelligent systems using type-2 fuzzy logic and soft computing (SC) techniques. The authors extend the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each technique offers. This book is intended to be a major reference tool and can be used as a textbook.

Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

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Publisher : CRC Press
ISBN 13 : 1000715124
Total Pages : 363 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms by : Lakhmi C. Jain

Download or read book Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms written by Lakhmi C. Jain and published by CRC Press. This book was released on 2020-01-29 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks can mimic the biological information-processing mechanism in - a very limited sense. Fuzzy logic provides a basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise in solving problems, but a definitive theoretical basis does not yet exist for their design. Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms integrates neural net, fuzzy system, and evolutionary computing in system design that enables its readers to handle complexity - offsetting the demerits of one paradigm by the merits of another. This book presents specific projects where fusion techniques have been applied. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural networks, fuzzy control, and evolutionary computing techniques in modern engineering systems. These specific applications include: direct frequency converters electro-hydraulic systems motor control toaster control speech recognition vehicle routing fault diagnosis Asynchronous Transfer Mode (ATM) communications networks telephones for hard-of-hearing people control of gas turbine aero-engines telecommunications systems design Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms covers the spectrum of applications - comprehensively demonstrating the advantages of fusion techniques in industrial applications.

Fundamentals of Computational Intelligence

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Publisher : John Wiley & Sons
ISBN 13 : 111921436X
Total Pages : 378 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Fundamentals of Computational Intelligence by : James M. Keller

Download or read book Fundamentals of Computational Intelligence written by James M. Keller and published by John Wiley & Sons. This book was released on 2016-07-13 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.

Advances in Metaheuristics

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Publisher : CRC Press
ISBN 13 : 1315297639
Total Pages : 182 pages
Book Rating : 4.3/5 (152 download)

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Book Synopsis Advances in Metaheuristics by : Timothy Ganesan

Download or read book Advances in Metaheuristics written by Timothy Ganesan and published by CRC Press. This book was released on 2016-11-28 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Metaheuristics: Applications in Engineering Systems provides details on current approaches utilized in engineering optimization. It gives a comprehensive background on metaheuristic applications, focusing on main engineering sectors such as energy, process, and materials. It discusses topics such as algorithmic enhancements and performance measurement approaches, and provides insights into the implementation of metaheuristic strategies to multi-objective optimization problems. With this book, readers can learn to solve real-world engineering optimization problems effectively using the appropriate techniques from emerging fields including evolutionary and swarm intelligence, mathematical programming, and multi-objective optimization. The ten chapters of this book are divided into three parts. The first part discusses three industrial applications in the energy sector. The second focusses on process optimization and considers three engineering applications: optimization of a three-phase separator, process plant, and a pre-treatment process. The third and final part of this book covers industrial applications in material engineering, with a particular focus on sand mould-systems. It also includes discussions on the potential improvement of algorithmic characteristics via strategic algorithmic enhancements. This book helps fill the existing gap in literature on the implementation of metaheuristics in engineering applications and real-world engineering systems. It will be an important resource for engineers and decision-makers selecting and implementing metaheuristics to solve specific engineering problems.

Introduction to Neural Networks, Fuzzy Logic & Genetic Algorithms

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Publisher :
ISBN 13 : 9788184950793
Total Pages : 0 pages
Book Rating : 4.9/5 (57 download)

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Book Synopsis Introduction to Neural Networks, Fuzzy Logic & Genetic Algorithms by : Sudarshan K. Valluru

Download or read book Introduction to Neural Networks, Fuzzy Logic & Genetic Algorithms written by Sudarshan K. Valluru and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: