Hybrid Competitive Learning Method Using The Fireworks Algorithm And Artificial Neural Networks

Author : Fevrier Valdez
Publisher : Springer Nature
ISBN 13 : 303147712X
Total Pages : 112 pages
Book Rating : 4.26/5 ( download)

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Download or read book Hybrid Competitive Learning Method Using the Fireworks Algorithm and Artificial Neural Networks written by Fevrier Valdez and published by Springer Nature. This book was released on 2023-11-25 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the fields of neural networks, swarm optimization algorithms, clustering and fuzzy logic. This book describes a hybrid method with three different techniques of intelligence computation: neural networks, optimization algorithms and fuzzy logic. Within the neural network techniques, competitive neural networks (CNNs) are used, for the optimization algorithms technique, we used the fireworks algorithm (FWA), and in the area of fuzzy logic, the Type-1 Fuzzy Inference Systems (T1FIS) and the Interval Type-2 Fuzzy Inference Systems (IT2FIS) were used, with their variants of Mamdani and Sugeno type, respectively. FWA was adapted for data clustering with the goal to help of competitive neural network to find the optimal number of neurons. It is important to mention that two variants were applied to the FWA: dynamically adjust of parameters with Type-1 Fuzzy Logic (FFWA) as the first one and Interval Type-2 (F2FWA) as the second one. Subsequently, based on the outputs of the CNN and with the goal of classification data, we designed Type-1 and Interval Type-2 Fuzzy Inference Systems of Mamdani and Sugeno type. This book is intended to be a reference for scientists and engineers interested in applying a different metaheuristic or an artificial neural network in order to solve optimization and applied fuzzy logic techniques for solving problems in clustering and classification data. This book is also used as a reference for graduate courses like the following: soft computing, swarm optimization algorithms, clustering data, fuzzy classify and similar ones. We consider that this book can also be used to get novel ideas for new lines of research, new techniques of optimization or to continue the lines of the research proposed by the authors of the book.

Author : Fouad Sabry
Publisher : One Billion Knowledgeable
ISBN 13 :
Total Pages : 132 pages
Book Rating : 4.75/5 ( download)

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Download or read book Competitive Learning written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-06-21 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Competitive Learning In artificial neural networks, competitive learning is a type of unsupervised learning in which nodes fight for the right to respond to a subset of the input data. This type of learning is known as "competitive learning." Competitive learning is a form of learning that is similar to Hebbian learning. It operates by raising the level of specialization at each node in the network. It works quite well for discovering clusters hidden within data. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Competitive Learning Chapter 2: Self-organizing map Chapter 3: Perceptron Chapter 4: Unsupervised Learning Chapter 5: Hebbian Theory Chapter 6: Backpropagation Chapter 7: Multilayer Perceptron Chapter 8: Learning Rule Chapter 9: Feature Learning Chapter 10: Types of artificial neural networks (II) Answering the public top questions about competitive learning. (III) Real world examples for the usage of competitive learning in many fields. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of competitive learning. What Is Artificial Intelligence Series The artificial intelligence book series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The artificial intelligence book series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.

Author : Stefan Wermter
Publisher : Springer
ISBN 13 : 3540464174
Total Pages : 411 pages
Book Rating : 4.74/5 ( download)

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Download or read book Hybrid Neural Systems written by Stefan Wermter and published by Springer. This book was released on 2006-12-30 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hybrid neural systems are computational systems which are based mainly on artificial neural networks and allow for symbolic interpretation or interaction with symbolic components. This book is derived from a workshop held during the NIPS'98 in Denver, Colorado, USA, and competently reflects the state of the art of research and development in hybrid neural systems. The 26 revised full papers presented together with an introductory overview by the volume editors have been through a twofold process of careful reviewing and revision. The papers are organized in the following topical sections: structured connectionism and rule representation; distributed neural architectures and language processing; transformation and explanation; robotics, vision, and cognitive approaches.

Author : Michael Zgurovsky
Publisher : Springer Nature
ISBN 13 : 303048453X
Total Pages : 527 pages
Book Rating : 4.38/5 ( download)

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Download or read book Artificial Intelligence Systems Based on Hybrid Neural Networks written by Michael Zgurovsky and published by Springer Nature. This book was released on 2020-09-03 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for specialists as well as students and graduate students in the field of artificial intelligence, robotics and information technology. It is will also appeal to a wide range of readers interested in expanding the functionality of artificial intelligence systems. One of the pressing problems of modern artificial intelligence systems is the development of integrated hybrid systems based on deep learning. Unfortunately, there is currently no universal methodology for developing topologies of hybrid neural networks (HNN) using deep learning. The development of such systems calls for the expansion of the use of neural networks (NS) for solving recognition, classification and optimization problems. As such, it is necessary to create a unified methodology for constructing HNN with a selection of models of artificial neurons that make up HNN, gradually increasing the complexity of their structure using hybrid learning algorithms.

Author : Anand J. Kulkarni
Publisher : Springer Nature
ISBN 13 : 9811509948
Total Pages : 202 pages
Book Rating : 4.40/5 ( download)

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Download or read book Optimization in Machine Learning and Applications written by Anand J. Kulkarni and published by Springer Nature. This book was released on 2019-11-29 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.

Author : Nilanjan Dey
Publisher : Springer Nature
ISBN 13 : 9813361042
Total Pages : 239 pages
Book Rating : 4.41/5 ( download)

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Download or read book Applications of Flower Pollination Algorithm and its Variants written by Nilanjan Dey and published by Springer Nature. This book was released on 2021-03-17 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents essential concepts of traditional Flower Pollination Algorithm (FPA) and its recent variants and also its application to find optimal solution for a variety of real-world engineering and medical problems. Swarm intelligence-based meta-heuristic algorithms are extensively implemented to solve a variety of real-world optimization problems due to its adaptability and robustness. FPA is one of the most successful swarm intelligence procedures developed in 2012 and extensively used in various optimization tasks for more than a decade. The mathematical model of FPA is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, FPA has attracted attention of researchers, who are working to find the optimal solutions in variety of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization, and linear/nonlinear optimization problems. Along with the traditional bat algorithm, the enhanced versions of FPA are also considered to solve a variety of optimization problems in science, engineering, and medical applications.

Author : M. Ananda Rao
Publisher : Alpha Science Int'l Ltd.
ISBN 13 : 9781842651315
Total Pages : 260 pages
Book Rating : 4.15/5 ( download)

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Download or read book Neural Networks written by M. Ananda Rao and published by Alpha Science Int'l Ltd.. This book was released on 2003 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Oscar Castillo
Publisher : Springer Nature
ISBN 13 : 3030341356
Total Pages : 354 pages
Book Rating : 4.50/5 ( download)

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Download or read book Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine written by Oscar Castillo and published by Springer Nature. This book was released on 2019-11-23 with total page 354 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 combinations, and their applications in areas such as: intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems. The book is divided into five main parts. The first part proposes new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications; the second explores new concepts and algorithms in neural networks and fuzzy logic applied to recognition. The third part examines the theory and practice of meta-heuristics in various areas of application, while the fourth highlights diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical contexts. Finally, the fifth part focuses on applications of fuzzy logic, neural networks and meta-heuristics to robotics problems.

Author : Patricia Melin
Publisher : Springer
ISBN 13 : 331947054X
Total Pages : 838 pages
Book Rating : 4.42/5 ( download)

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Download or read book Nature-Inspired Design of Hybrid Intelligent Systems written by Patricia Melin and published by Springer. This book was released on 2016-12-08 with total page 838 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights recent advances in the design of hybrid intelligent systems based on 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 divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book’s third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.

Author : Tan, Ying
Publisher : IGI Global
ISBN 13 : 1799816605
Total Pages : 471 pages
Book Rating : 4.07/5 ( download)

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Download or read book Handbook of Research on Fireworks Algorithms and Swarm Intelligence written by Tan, Ying and published by IGI Global. This book was released on 2019-12-27 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, swarm intelligence has become a popular computational approach among researchers working on optimization problems throughout the globe. Several algorithms inside swarm intelligence have been implemented due to their application to real-world issues and other advantages. A specific procedure, Fireworks Algorithm, is an emerging method that studies the explosion process of fireworks within local areas. Applications of this developing program are undiscovered, and research is necessary for scientists to fully understand the workings of this innovative system. The Handbook of Research on Fireworks Algorithms and Swarm Intelligence is a pivotal reference source that provides vital research on theory analysis, improvements, and applications of fireworks algorithm. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores up-to-date progress on the specific techniques of this algorithm. This book is ideally designed for researchers, data scientists, mathematicians, engineers, software developers, postgraduates, and academicians seeking coverage on this evolutionary computation method.