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NEURAL NETWORKS IN DESIGN AND MANUFACTURING
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NEURAL NETWORKS IN DESIGN AND MANUFACTURING
Author:AL WANG JUN ET (EN)
A introductory fragment is available
Language of a book: Английский
Publisher: Gardners Books

    Over the past few years, there has been a surge of research activities on artificial neural networks. Although the thrust originally came from computer scientists and electrical engineers, neural network research has recently attracted researchers in the fields of operations research, operations management and industrial engineering.Despite the huge volume of recent publications devoted to neural network research, there is no single monograph addressing the potential roles of artificial neural networks for design and manufacturing.The focus of this book is on the applications of neural network concepts and techniques to design and manufacturing. This book reviews the state-of-the-art of the research activities, highlights the recent advances in research and development, and discusses the potential directions and future trends along this stream of research.The potential readers of this book will include, but are not limited to, beginners, professionals and practitioners in industries who are applying neural networks to design and manufacturing.The topics include conceptual design, group technology, process planning and scheduling, process monitoring and others.Contents:A Neural Network Approach to Group TechnologyNeuro-Clustering for Group TechnologyA Parallel and Distributed Processing Algorithm for Facility LayoutNeural Networks in Conceptual DesignKnowledge Acquisition in Neural Networks and Expert Systems: The Case of Packer Selection in Oil Well DesignSetup Generation and Feature Sequencing Using an Unsupervised Learning AlgorithmScheduling Computation Tasks onto a Multiprocessor System by Mean Field Annealing of a Hopfield Neural NetworkMulti-Functional Neural Networks for System IdentificationNeural network Applications in On-Line Monitoring of a Turning ProcessNeural Adaptive Systems for Machining Errors ModelingReadership: Engineers, computer scientists and practitioners in industries.Key Features:Contains research and analyses on the multi-dimensional re-polarization process by scholars from multiple disciplinesDiscusses the different drivers of the re-polarization processHighlights special issues salient to the outcomes of the re-polarization process

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