Hybrid Neural Network and Expert Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hybrid Neural Network and Expert Systems write by Larry R. Medsker. This book was released on 2012-12-06. Hybrid Neural Network and Expert Systems available in PDF, EPUB and Kindle. 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.
Neural Network Learning and Expert Systems
Neural Network Learning and Expert Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Network Learning and Expert Systems write by Stephen I. Gallant. This book was released on 1993. Neural Network Learning and Expert Systems available in PDF, EPUB and Kindle. presents a unified and in-depth development of neural network learning algorithms and neural network expert systems
Hybrid Intelligent Systems
Hybrid Intelligent Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hybrid Intelligent Systems write by Larry R. Medsker. This book was released on 2012-12-06. Hybrid Intelligent Systems available in PDF, EPUB and Kindle. 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.
Hybrid Neural Systems
Hybrid Neural Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hybrid Neural Systems write by Stefan Wermter. This book was released on 2006-12-30. Hybrid Neural Systems available in PDF, EPUB and Kindle. 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.
Artificial Intelligence Systems Based on Hybrid Neural Networks
Artificial Intelligence Systems Based on Hybrid Neural Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Intelligence Systems Based on Hybrid Neural Networks write by Michael Zgurovsky. This book was released on 2020-09-03. Artificial Intelligence Systems Based on Hybrid Neural Networks available in PDF, EPUB and Kindle. 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.
