Nature Inspired Optimization Of Type 2 Fuzzy Neural Hybrid Models For Classification In Medical Diagnosis

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Nature-inspired Optimization of Type-2 Fuzzy Neural Hybrid Models for Classification in Medical Diagnosis

Author : Patricia Melin
Publisher : Springer Nature
ISBN 13 : 3030822192
Total Pages : 134 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Nature-inspired Optimization of Type-2 Fuzzy Neural Hybrid Models for Classification in Medical Diagnosis by : Patricia Melin

Download or read book Nature-inspired Optimization of Type-2 Fuzzy Neural Hybrid Models for Classification in Medical Diagnosis written by Patricia Melin and published by Springer Nature. This book was released on 2021-08-06 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the utilization of different soft computing techniques and their optimization for providing an accurate and efficient medical diagnosis. The proposed method provides a precise and timely diagnosis of the risk that a person has to develop a particular disease, but it can be adaptable to provide the diagnosis of different diseases. This book reflects the experimentation that was carried out, based on the different optimizations using bio-inspired algorithms (such as bird swarm algorithm, flower pollination algorithms, and others). In particular, the optimizations were carried out to design the fuzzy classifiers of the nocturnal blood pressure profile and heart rate level. In addition, to obtain the architecture that provides the best result, the neurons and the number of neurons per layers of the artificial neural networks used in the model are optimized. Furthermore, different tests were carried out with the complete optimized model. Another work that is presented in this book is the dynamic parameter adaptation of the bird swarm algorithm using fuzzy inference systems, with the aim of improving its performance. For this, different experiments are carried out, where mathematical functions and a monolithic neural network are optimized to compare the results obtained with the original algorithm. The book will be of interest for graduate students of engineering and medicine, as well as researchers and professors aiming at proposing and developing new intelligent models for medical diagnosis. In addition, it also will be of interest for people working on metaheuristic algorithms and their applications on medicine.

Neuro Fuzzy Hybrid Models for Classification in Medical Diagnosis

Author : Patricia Melin
Publisher : Springer Nature
ISBN 13 : 3030604810
Total Pages : 109 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Neuro Fuzzy Hybrid Models for Classification in Medical Diagnosis by : Patricia Melin

Download or read book Neuro Fuzzy Hybrid Models for Classification in Medical Diagnosis written by Patricia Melin and published by Springer Nature. This book was released on 2020-10-27 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is focused on the use of intelligent techniques, such as fuzzy logic, neural networks and bio-inspired algorithms, and their application in medical diagnosis. The main idea is that the proposed method may be able to adapt to medical diagnosis problems in different possible areas of the medicine and help to have an improvement in diagnosis accuracy considering a clinical monitoring of 24 hours or more of the patient. In this book, tests were made with different architectures proposed in the different modules of the proposed model. First, it was possible to obtain the architecture of the fuzzy classifiers for the level of blood pressure and for the pressure load, and these were optimized with the different bio-inspired algorithms (Genetic Algorithm and Chicken Swarm Optimization). Secondly, we tested with a local database of 300 patients and good results were obtained. It is worth mentioning that this book is an important part of the proposed general model; for this reason, we consider that these modules have a good performance in a particular way, but it is advisable to perform more tests once the general model is completed.

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

Author : Oscar Castillo
Publisher : Springer Nature
ISBN 13 : 3030354458
Total Pages : 767 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 767 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.

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

Author : Oscar Castillo
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.

Nature-Inspired Methods for Smart Healthcare Systems and Medical Data

Author : Ahmed M. Anter
Publisher : Springer Nature
ISBN 13 : 3031459520
Total Pages : 265 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Nature-Inspired Methods for Smart Healthcare Systems and Medical Data by : Ahmed M. Anter

Download or read book Nature-Inspired Methods for Smart Healthcare Systems and Medical Data written by Ahmed M. Anter and published by Springer Nature. This book was released on 2024-01-02 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to gather high-quality research papers on developing theories, frameworks, architectures, and algorithms for solving complex challenges in smart healthcare applications for real industry use. It explores the recent theoretical and practical applications of metaheuristics and optimization in various smart healthcare contexts. The book also discusses the capability of optimization techniques to obtain optimal parameters in ML and DL technologies. It provides an open platform for academics and engineers to share their unique ideas and investigate the potential convergence of existing systems and advanced metaheuristic algorithms. The book's outcome will enable decision-makers and practitioners to select suitable optimization approaches for scheduling patients in crowded environments with minimized human errors. The healthcare system aims to improve the lives of disabled, elderly, sick individuals, and children. IoT-based systems simplify decision-making and task automation, offering an automated foundation. Nature-inspired metaheuristics and mining algorithms are crucial for healthcare applications, reducing costs, increasing efficiency, enabling accurate data analysis, and enhancing patient care. Metaheuristics improve algorithm performance and address challenges in data mining and ML, making them essential in healthcare research. Real-time IoT-based healthcare systems can be modeled using an IoT-based metaheuristic approach to generate optimal solutions. Metaheuristics are powerful technologies for optimization problems in healthcare systems. They balance exact methods, which guarantee optimal solutions but require significant computational resources, with fast but low-quality greedy methods. Metaheuristic algorithms find better solutions while minimizing computational time. The scientific community is increasingly interested in metaheuristics, incorporating techniques from AI, operations research, and soft computing. New metaheuristics offer efficient ways to address optimization problems and tackle unsolved challenges. They can be parameterized to control performance and adjust the trade-off between solution quality and resource utilization. Metaheuristics manage the trade-off between performance and solution quality, making them highly applicable to real-time applications with pragmatic objectives.

Advanced Computational Intelligence Methods for Processing Brain Imaging Data

Author : Kaijian Xia
Publisher : Frontiers Media SA
ISBN 13 : 2832504620
Total Pages : 754 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Advanced Computational Intelligence Methods for Processing Brain Imaging Data by : Kaijian Xia

Download or read book Advanced Computational Intelligence Methods for Processing Brain Imaging Data written by Kaijian Xia and published by Frontiers Media SA. This book was released on 2022-11-09 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems

Author : Kose, Utku
Publisher : IGI Global
ISBN 13 : 1522547703
Total Pages : 411 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems by : Kose, Utku

Download or read book Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems written by Kose, Utku and published by IGI Global. This book was released on 2018-03-31 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological tools and computational techniques have enhanced the healthcare industry. These advancements have led to significant progress and novel opportunities for biomedical engineering. Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems is a pivotal reference source for emerging scholarly research on trends and techniques in the utilization of nature-inspired approaches in biomedical engineering. Featuring extensive coverage on relevant areas such as artificial intelligence, clinical decision support systems, and swarm intelligence, this publication is an ideal resource for medical practitioners, professionals, students, engineers, and researchers interested in the latest developments in biomedical technologies.

Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms

Author : Dash, Sujata
Publisher : IGI Global
ISBN 13 : 152252858X
Total Pages : 567 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms by : Dash, Sujata

Download or read book Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms written by Dash, Sujata and published by IGI Global. This book was released on 2017-08-10 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems. The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.

Type-2 Fuzzy Logic: Theory and Applications

Author : Oscar Castillo
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.

Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization

Author : Patricia Melin
Publisher : Springer
ISBN 13 : 3319177478
Total Pages : 612 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization by : Patricia Melin

Download or read book Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization written by Patricia Melin and published by Springer. This book was released on 2015-06-12 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances on the design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization and their application in areas such as, intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in eight main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on fuzzy systems. The second part contains papers with the main theme of neural networks theory, which are basically papers dealing with new concepts and algorithms in neural networks. The third part contains papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The fourth part contains papers describing new nature-inspired optimization algorithms. The fifth part presents diverse applications of nature-inspired optimization algorithms. The sixth part contains papers describing new optimization algorithms. The seventh part contains papers describing applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. Finally, the eighth part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques.

Soft Computing for Recognition Based on Biometrics

Author : Patricia Melin
Publisher : Springer Science & Business Media
ISBN 13 : 3642151108
Total Pages : 449 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Soft Computing for Recognition Based on Biometrics by : Patricia Melin

Download or read book Soft Computing for Recognition Based on Biometrics written by Patricia Melin and published by Springer Science & Business Media. This book was released on 2010-09-20 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes bio-inspired models and applications of hybrid intelligent systems using soft computing techniques for image analysis and pattern recognition based on biometrics and other sources. Each section groups papers on a similar subject.

Soft-Computing-Based Nonlinear Control Systems Design

Author : Singh, Uday Pratap
Publisher : IGI Global
ISBN 13 : 1522535322
Total Pages : 409 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Soft-Computing-Based Nonlinear Control Systems Design by : Singh, Uday Pratap

Download or read book Soft-Computing-Based Nonlinear Control Systems Design written by Singh, Uday Pratap and published by IGI Global. This book was released on 2018-02-09 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: A critical part of ensuring that systems are advancing alongside technology without complications is problem solving. Practical applications of problem-solving theories can model conflict and cooperation and aid in creating solutions to real-world problems. Soft-Computing-Based Nonlinear Control Systems Design is a critical scholarly publication that examines the practical applications of control theory and its applications in problem solving to fields including economics, environmental management, and financial modelling. Featuring a wide range of topics, such as fuzzy logic, nature-inspired algorithms, and cloud computing, this book is geared toward academicians, researchers, and students seeking relevant research on control theory and its practical applications.

NEURAL NETWORKS, FUZZY SYSTEMS AND EVOLUTIONARY ALGORITHMS : SYNTHESIS AND APPLICATIONS

Author : S. RAJASEKARAN
Publisher : PHI Learning Pvt. Ltd.
ISBN 13 : 812035334X
Total Pages : 574 pages
Book Rating : 4.1/5 (23 download)

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Book Synopsis NEURAL NETWORKS, FUZZY SYSTEMS AND EVOLUTIONARY ALGORITHMS : SYNTHESIS AND APPLICATIONS by : S. RAJASEKARAN

Download or read book NEURAL NETWORKS, FUZZY SYSTEMS AND EVOLUTIONARY ALGORITHMS : SYNTHESIS AND APPLICATIONS written by S. RAJASEKARAN and published by PHI Learning Pvt. Ltd.. This book was released on 2017-05-01 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this book provides a comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence, which in recent years, has turned synonymous to it. The constituent technologies discussed comprise neural network (NN), fuzzy system (FS), evolutionary algorithm (EA), and a number of hybrid systems, which include classes such as neuro-fuzzy, evolutionary-fuzzy, and neuro-evolutionary systems. The hybridization of the technologies is demonstrated on architectures such as fuzzy backpropagation network (NN-FS hybrid), genetic algorithm-based backpropagation network (NN-EA hybrid), simplified fuzzy ARTMAP (NN-FS hybrid), fuzzy associative memory (NN-FS hybrid), fuzzy logic controlled genetic algorithm (EA-FS hybrid) and evolutionary extreme learning machine (NN-EA hybrid) 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 the courses in soft computing at both the senior undergraduate and first-year postgraduate levels of computer science and engineering. It should also be of interest to researchers and technologists desirous of applying soft computing technologies to their respective fields of work.

Nature-Inspired Optimization Algorithms

Author : Xin-She Yang
Publisher : Elsevier
ISBN 13 : 0124167454
Total Pages : 277 pages
Book Rating : 4.1/5 (241 download)

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Book Synopsis Nature-Inspired Optimization Algorithms by : Xin-She Yang

Download or read book Nature-Inspired Optimization Algorithms written by Xin-She Yang and published by Elsevier. This book was released on 2014-02-17 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. - Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature - Provides a theoretical understanding as well as practical implementation hints - Provides a step-by-step introduction to each algorithm

Recent Advances in Swarm Intelligence and Evolutionary Computation

Author : Xin-She Yang
Publisher : Springer
ISBN 13 : 331913826X
Total Pages : 295 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Recent Advances in Swarm Intelligence and Evolutionary Computation by : Xin-She Yang

Download or read book Recent Advances in Swarm Intelligence and Evolutionary Computation written by Xin-She Yang and published by Springer. This book was released on 2014-12-27 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference for graduates, lecturers, engineers and researchers in computer science, evolutionary computing, artificial intelligence, machine learning, computational intelligence, data mining, engineering optimization and designs.

Intelligent Systems

Author : Bogdan M. Wilamowski
Publisher : CRC Press
ISBN 13 : 143980284X
Total Pages : 610 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Intelligent Systems by : Bogdan M. Wilamowski

Download or read book Intelligent Systems written by Bogdan M. Wilamowski and published by CRC Press. This book was released on 2018-10-03 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Industrial Electronics Handbook, Second Edition combines traditional and newer, more specialized knowledge that will help industrial electronics engineers develop practical solutions for the design and implementation of high-power applications. Embracing the broad technological scope of the field, this collection explores fundamental areas, including analog and digital circuits, electronics, electromagnetic machines, signal processing, and industrial control and communications systems. It also facilitates the use of intelligent systems—such as neural networks, fuzzy systems, and evolutionary methods—in terms of a hierarchical structure that makes factory control and supervision more efficient by addressing the needs of all production components. Enhancing its value, this fully updated collection presents research and global trends as published in the IEEE Transactions on Industrial Electronics Journal, one of the largest and most respected publications in the field. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have made substantial contributions to the solution of very complex problems. As a result, the field of computational intelligence has branched out in several directions. For instance, artificial neural networks can learn how to classify patterns, such as images or sequences of events, and effectively model complex nonlinear systems. Simple and easy to implement, fuzzy systems can be applied to successful modeling and system control. Illustrating how these and other tools help engineers model nonlinear system behavior, determine and evaluate system parameters, and ensure overall system control, Intelligent Systems: Addresses various aspects of neural networks and fuzzy systems Focuses on system optimization, covering new techniques such as evolutionary methods, swarm, and ant colony optimizations Discusses several applications that deal with methods of computational intelligence Other volumes in the set: Fundamentals of Industrial Electronics Power Electronics and Motor Drives Control and Mechatronics Industrial Communication Systems

Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

Author : Lakhmi C. Jain
Publisher : CRC Press
ISBN 13 : 1000722945
Total Pages : 366 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 366 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.