Neural Network Systems Techniques and Applications, Seven-Volume Set: Industrial and Manufacturing Systems, Volume 4

Neural Network Systems Techniques and Applications, Seven-Volume Set: Industrial and Manufacturing Systems, Volume 4 Review

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Neural Network Systems Techniques and Applications, Seven-Volume Set: Industrial and Manufacturing Systems, Volume 4 Feature

Industrial and Manufacturing Systems serves as an in-depth guide to major applications in this focal area of interest to the engineering community. This volume emphasizes the neural network structures used to achieve practical and effective systems, and provides numerous examples. Industrial and Manufacturing Systems is a unique and comprehensive reference to diverse application methodologies and implementations by means of neural network systems. It willbe of use to practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as in computer science and engineering.

Key Features
* Quality control techniques
* Active noise and vibration control
* Chemical processing systems
* Process monitoring and diagnosis
* Robotic assembly in electronics manufacturing systems
* Smart structural systems of improved effective-ness
* Closed loop feedback control in uncertain nonlinear manufacturing systems
* Adaptive neural controllers in industrial systems
* Machine tool control systems
Emphasis is placed on neural network structures for achieving practical and effective systems, with numerous examples illustrating the text; Practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as in computer science and engineering, will find this volume a unique and comprehensive reference to diverse application methodologies and implementations by means of neura network systems.

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Composite Materials Technology: Neural Network Applications

Composite Materials Technology: Neural Network Applications Review

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Composite Materials Technology: Neural Network Applications Feature

Artificial neural networks (ANN) can provide new insight into the study of composite materials and can normally be combined with other artificial intelligence tools such as expert system, genetic algorithm, and fuzzy logic. Because research on this field is very new, there is only a limited amount of published literature on the subject.
Compiling information from diverse sources, Composite Materials Technology: Neural Network Applications fills the void in knowledge of these important networks, covering composite mechanics, materials characterization, product design, and other important aspects of polymer matrix composites.
Light weight, corrosion resistance, good stiffness and strength properties, and part consolidation are just some of the reasons that composites are useful in areas including civil engineering and structure, chemical processing, management, agriculture, space study, and manufacturing. ANN has already been used to carry out design prediction, mechanical property prediction, and selection processes in the evolution of composites, but although it has already been used with great success in various branches of scientific and technological research, it is still in the nascent stage of its development.
Featuring contributions from leading researchers throughout the world, this book is divided into four parts, starting with an introduction to neural networks and a review of existing literature on the subject. The text then covers structural health monitoring and damage detection in composites, addresses mechanical properties, and discusses design, analysis, and materials selection. Training, testing, and validation of experimental data were carried out to optimize the results presented in the book.
This book will be an important aid to researchers as they work on the future implementation of ANN in industries such as aerospace, automotive, marine, sporting goods, furniture, and electronics and communication.

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