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This book is indexed in
Computer and Information Science » Numerical Analysis and Scientific Computing
Artificial Neural Networks - Industrial and Control Engineering Applications
Edited by Kenji Suzuki, ISBN 978-953-307-220-3, Hard cover, 478 pages, Publisher: InTech, Chapters published April 04, 2011 under CC BY-NC-SA 3.0 license
DOI: 10.5772/2041
Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications. The purpose of this book is to provide recent advances of artificial neural networks in industrial and control engineering applications. The book begins with a review of applications of artificial neural networks in textile industries. Particular applications in textile industries follow. Parts continue with applications in materials science and industry such as material identification, and estimation of material property and state, food industry such as meat, electric and power industry such as batteries and power systems, mechanical engineering such as engines and machines, and control and robotic engineering such as system control and identification, fault diagnosis systems, and robot manipulation. Thus, this book will be a fundamental source of recent advances and applications of artificial neural networks in industrial and control engineering areas. The target audience includes professors and students in engineering schools, and researchers and engineers in industries.
- Chapter 1
Review of Application of Artificial Neural Networks in Textiles and Clothing Industries over Last Decades - Chapter 2
Artificial Neural Network Prosperities in Textile Applications - Chapter 3
Modelling of Needle-Punched Nonwoven Fabric Properties Using Artificial Neural Network - Chapter 4
Artificial Neural Networks for Material Identification, Mineralogy and Analytical Geochemistry Based on Laser-Induced Breakdown Spectroscopy - Chapter 5
Application of Artificial Neural Networks in the Estimation of Mechanical Properties of Materials - Chapter 6
Optimum Design and Application of Nano-Micro-Composite Ceramic Tool and Die Materials with Improved Back Propagation Neural Network - Chapter 7
Application of Bayesian Neural Networks to Predict Strength and Grain Size of Hot Strip Low Carbon Steels - Chapter 8
Adaptive Neuro-Fuzzy Inference System Prediction of Calorific Value Based on the Analysis of U.S. Coals - Chapter 9
Artificial Neural Network Applied for Detecting the Saturation Level in the Magnetic Core of a Welding Transformer - Chapter 10
Application of Artificial Neural Networks to Food and Fermentation Technology - Chapter 11
Application of Artificial Neural Networks in Meat Production and Technology - Chapter 12
State of Charge Estimation of Ni-MH battery pack by using ANN - Chapter 13
A Novel Frequency Tracking Method Based on Complex Adaptive Linear Neural Network State Vector in Power Systems - Chapter 14
Application of ANN to Real and Reactive Power Allocation Scheme - Chapter 15
The Applications of Artificial Neural Networks to Engines - Chapter 16
A Comparison of Speed-Feed Fuzzy Intelligent System and ANN for Machinability Data Selection of CNC Machines - Chapter 17
Artificial Neural Network – Possible Approach to Nonlinear System Control - Chapter 18
Direct Neural Network Control via Inverse Modelling: Application on Induction Motors - Chapter 19
System Identification of NN-based Model Reference Control of RUAV during Hover - Chapter 20
Intelligent Vibration Signal Diagnostic System Using Artificial Neural Network - Chapter 21
Conditioning Monitoring and Fault Diagnosis for a Servo-Pneumatic System with Artificial Neural Network Algorithms - Chapter 22
Neural Networks’ Based Inverse Kinematics Solution for Serial Robot Manipulators Passing Through Singularities
