Hybrid Neural Network And Expert Systems
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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 Intelligent Systems
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Author : Larry R. Medsker
language : en
Publisher: Springer
Release Date : 1995-06-30
Hybrid Intelligent Systems written by Larry R. Medsker and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-06-30 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.
A Hybrid Object Oriented Environment Integrating Neural Networks And Expert Systems
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Author : Sukhdev Singh Khebbal
language : en
Publisher:
Release Date : 1995
A Hybrid Object Oriented Environment Integrating Neural Networks And Expert Systems written by Sukhdev Singh Khebbal and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with categories.
Hybrid Architectures For Intelligent Systems
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Author : Abraham Kandel
language : en
Publisher: CRC Press
Release Date : 2020-09-10
Hybrid Architectures For Intelligent Systems written by Abraham Kandel and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-10 with Computers categories.
Hybrid architecture for intelligent systems is a new field of artificial intelligence concerned with the development of the next generation of intelligent systems. This volume is the first book to delineate current research interests in hybrid architectures for intelligent systems. The book is divided into two parts. The first part is devoted to the theory, methodologies, and algorithms of intelligent hybrid systems. The second part examines current applications of intelligent hybrid systems in areas such as data analysis, pattern classification and recognition, intelligent robot control, medical diagnosis, architecture, wastewater treatment, and flexible manufacturing systems. Hybrid Architectures for Intelligent Systems is an important reference for computer scientists and electrical engineers involved with artificial intelligence, neural networks, parallel processing, robotics, and systems architecture.
Expert Systems
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Author : Nikolopoulos
language : en
Publisher: CRC Press
Release Date : 1997-01-10
Expert Systems written by Nikolopoulos and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-01-10 with Technology & Engineering categories.
Offering an introduction to the field of expert/knowledge based systems, this text covers current and emerging trends as well as future research areas. It considers both the system shell and programming environment approaches to expert system development.
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 Intelligent Engineering Systems
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Author : L. C. Jain
language : en
Publisher: World Scientific
Release Date : 1997
Hybrid Intelligent Engineering Systems written by L. C. Jain and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Technology & Engineering categories.
This book on hybrid intelligent engineering systems is unique, in the sense that it presents the integration of expert systems, neural networks, fuzzy systems, genetic algorithms, and chaos engineering. It shows that these new techniques enhance the capabilities of one another. A number of hybrid systems for solving engineering problems are presented.
Hybrid Intelligent Systems
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Author : Ajith Abraham
language : en
Publisher: Springer Nature
Release Date : 2021-04-16
Hybrid Intelligent Systems written by Ajith Abraham and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-16 with Technology & Engineering categories.
This book highlights the recent research on hybrid intelligent systems and their various practical applications. It presents 58 selected papers from the 20th International Conference on Hybrid Intelligent Systems (HIS 2020) and 20 papers from the 12th World Congress on Nature and Biologically Inspired Computing (NaBIC 2020), which was held online, from December 14 to 16, 2020. A premier conference in the field of artificial intelligence, HIS - NaBIC 2020 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from 25 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of science and engineering.
Design And Development Of Expert Systems And Neural Networks
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Author : L. R. Medsker
language : en
Publisher: Prentice Hall
Release Date : 1994
Design And Development Of Expert Systems And Neural Networks written by L. R. Medsker and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Expert system (Computer science). categories.
This book gives readers and practitioners the tools they need to develop appropriate applications and systems. It also explores managing and institutionalizing expert system development and usage.
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.