Hybrid Neural Systems
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Hybrid Neural Systems
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Author : Stefan Wermter
language : en
Publisher: Springer
Release Date : 2006-12-30
Hybrid Neural Systems written by Stefan Wermter and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-30 with Medical categories.
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.
Hybrid Neural Systems
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Author : Stefan Wermter
language : en
Publisher: Springer
Release Date : 2000-03-29
Hybrid Neural Systems written by Stefan Wermter and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-03-29 with Medical categories.
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.
Hybrid Neural Network And Expert Systems
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Author : Larry R. Medsker
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Hybrid Neural Network And Expert Systems written by Larry R. Medsker and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Hybrid Neural Network and Expert Systems presents the basics of expert systems and neural networks, and the important characteristics relevant to the integration of these two technologies. Through case studies of actual working systems, the author demonstrates the use of these hybrid systems in practical situations. Guidelines and models are described to help those who want to develop their own hybrid systems. Neural networks and expert systems together represent two major aspects of human intelligence and therefore are appropriate for integration. Neural networks represent the visual, pattern-recognition types of intelligence, while expert systems represent the logical, reasoning processes. Together, these technologies allow applications to be developed that are more powerful than when each technique is used individually. Hybrid Neural Network and Expert Systems provides frameworks for understanding how the combination of neural networks and expert systems can produce useful hybrid systems, and illustrates the issues and opportunities in this dynamic field.
Hybrid Neural Networks
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2023-06-20
Hybrid Neural Networks written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-20 with Computers categories.
What Is Hybrid Neural Networks The phrase "hybrid neural network" can refer to either biological neural networks that interact with artificial neuronal models or artificial neural networks that also have a symbolic component. Both of these interpretations are possible. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Hybrid neural network Chapter 2: Connectionism Chapter 3: Computational neuroscience Chapter 4: Symbolic artificial intelligence Chapter 5: Neuromorphic engineering Chapter 6: Recurrent neural network Chapter 7: Neural network Chapter 8: Neuro-fuzzy Chapter 9: Spiking neural network Chapter 10: Hierarchical temporal memory (II) Answering the public top questions about hybrid neural networks. (III) Real world examples for the usage of hybrid neural networks 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 hybrid neural networks. 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.
Artificial Intelligence Systems Based On Hybrid Neural Networks
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Author : Michael Zgurovsky
language : en
Publisher: Springer Nature
Release Date : 2020-09-03
Artificial Intelligence Systems Based On Hybrid Neural Networks written by Michael Zgurovsky and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-03 with Technology & Engineering categories.
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.
Hybrid Intelligent Systems
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Author : Larry R. Medsker
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Hybrid Intelligent Systems written by Larry R. Medsker and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Hybrid Intelligent Systems summarizes the strengths and weaknesses of five intelligent technologies: fuzzy logic, genetic algorithms, case-based reasoning, neural networks and expert systems, reviewing the status and significance of research into their integration. Engineering and scientific examples and case studies are used to illustrate principles and application development techniques. The reader will gain a clear idea of the current status of hybrid intelligent systems and discover how to choose and develop appropriate applications. The book is based on a thorough literature search of recent publications on research and development in hybrid intelligent systems; the resulting 50-page reference section of the book is invaluable. The book starts with a summary of the five major intelligent technologies and of the issues in and current status of research into them. Each subsequent chapter presents a detailed discussion of a different combination of intelligent technologies, along with examples and case studies. Four chapters contain detailed case studies of working hybrid systems. The book enables the reader to: Describe the important concepts, strengths and limitations of each technology; Recognize and analyze potential problems with the application of hybrid systems; Choose appropriate hybrid intelligent solutions; Understand how applications are designed with any of the approaches covered; Choose appropriate commercial development shells or tools. An invaluable reference source for those who wish to apply intelligent systems techniques to their own problems.
Intelligent Hybrid Systems
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Author : Da Ruan
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Intelligent Hybrid Systems written by Da Ruan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms is an organized edited collection of contributed chapters covering basic principles, methodologies, and applications of fuzzy systems, neural networks and genetic algorithms. All chapters are original contributions by leading researchers written exclusively for this volume. This book reviews important concepts and models, and focuses on specific methodologies common to fuzzy systems, neural networks and evolutionary computation. The emphasis is on development of cooperative models of hybrid systems. Included are applications related to intelligent data analysis, process analysis, intelligent adaptive information systems, systems identification, nonlinear systems, power and water system design, and many others. Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms provides researchers and engineers with up-to-date coverage of new results, methodologies and applications for building intelligent systems capable of solving large-scale problems.
Hybrid Computational Intelligence
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Author : Siddhartha Bhattacharyya
language : en
Publisher: Academic Press
Release Date : 2020-03-05
Hybrid Computational Intelligence written by Siddhartha Bhattacharyya and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-05 with Computers categories.
Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems. Provides insights into the latest research trends in hybrid intelligent algorithms and architectures Focuses on the application of hybrid intelligent techniques for pattern mining and recognition, in big data analytics, and in human-computer interaction Features hybrid intelligent applications in biomedical engineering and healthcare informatics
Introduction To Hybrid Intelligent Networks
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Author : Zhi-Hong Guan
language : en
Publisher: Springer
Release Date : 2019-02-01
Introduction To Hybrid Intelligent Networks written by Zhi-Hong Guan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-01 with Computers categories.
This book covers the fundamental principles, new theories and methodologies, and potential applications of hybrid intelligent networks. Chapters focus on hybrid neural networks and networked multi-agent networks, including their communication, control and optimization synthesis. This text also provides a succinct but useful guideline for designing neural network-based hybrid artificial intelligence for brain-inspired computation systems and applications in the Internet of Things. Artificial Intelligence has developed into a deep research field targeting robots with more brain-inspired perception, learning, decision-making abilities, etc. This text devoted to a tutorial on hybrid intelligent networks that have been identified in nature and engineering, especially in the brain, modeled by hybrid dynamical systems and complex networks, and have shown potential application to brain-inspired intelligence. Included in this text are impulsive neural networks, neurodynamics, multiagent networks, hybrid dynamics analysis, collective dynamics, as well as hybrid communication, control and optimization methods. Graduate students who are interested in artificial intelligence and hybrid intelligence, as well as professors and graduate students who are interested in neural networks and multiagent networks will find this textbook a valuable resource. AI engineers and consultants who are working in wireless communications and networking will want to buy this book. Also, professional and academic institutions in universities and Mobile vehicle companies and engineers and managers who concern humans in the loop of IoT will also be interested in this book.
Hybrid Information Systems
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Author : Ajith Abraham
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-08-06
Hybrid Information Systems written by Ajith Abraham and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-08-06 with Computers categories.
Hybrid intelligent systems are becoming a very important problem-solving methodology affecting researchers and practitioners in areas ranging from science and technology to business and commerce. This volume focuses on the hybridization of different soft computing technologies and their interactions with hard computing techniques, other intelligent computing frameworks, and agents. Topics covered include: genetic-neurocomputing, neuro-fuzzy systems, genetic-fuzzy systems, genetic-fuzzy neurocomputing, hybrid optimization techniques, interaction with intelligent agents, fusion of soft computing and hard computing techniques, other intelligent systems and hybrid systems applications. The different contributions were presented at the first international workshop on hybrid intelligent systems (HIS1) in Adelaide, Australia.