Ebook: Computational Intelligence: for Engineering and Manufacturing
Author: D. T. Pham P. T. N. Pham M. S. Packianather A. A. Afify (auth.) Diego Andina Duc Truong Pham (eds.)
- Tags: Computational Science and Engineering, Pattern Recognition, Circuits and Systems, Electronics and Microelectronics Instrumentation, Electronic and Computer Engineering
- Year: 2007
- Publisher: Springer US
- Edition: 1
- Language: English
- pdf
Unlike traditional computing, Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning.
All the contributors of this volume have direct bearing with this issue. From fundamentals to advanced systems as Multilayer Perceptron Artificial Neural Networks (ANN-MLP), Radial Basis Function Networks (RBF) and its relations with Fuzzy Sets and Support Vector Machines theory; and on to several critical applications in Engineering and Manufacturing. These are among applications where CI has excellent potential.
This volume has specially taken Neural Networks, key elements of CI, to the next level. Both novice and expert readers can benefit from this timely addition to CI based literature. Towards that goal, the editors and the authors have made critical contributions and succeeded. They have paved the road for learning paradigms towards the solution of many real-world problems.
Unlike traditional computing, Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning.
All the contributors of this volume have direct bearing with this issue. From fundamentals to advanced systems as Multilayer Perceptron Artificial Neural Networks (ANN-MLP), Radial Basis Function Networks (RBF) and its relations with Fuzzy Sets and Support Vector Machines theory; and on to several critical applications in Engineering and Manufacturing. These are among applications where CI has excellent potential.
This volume has specially taken Neural Networks, key elements of CI, to the next level. Both novice and expert readers can benefit from this timely addition to CI based literature. Towards that goal, the editors and the authors have made critical contributions and succeeded. They have paved the road for learning paradigms towards the solution of many real-world problems.
Content:
Front Matter....Pages I-XIII
Soft Computing and its Applications in Engineering and Manufacture....Pages 1-38
Neural Networks Historical Review....Pages 39-65
Artificial Neural Networks....Pages 67-92
Application of Neural Networks....Pages 93-108
Radial Basis Function Networks and their Application in Communication Systems....Pages 109-130
Biological Clues for Up-to-Date Artificial Neurons....Pages 131-146
Support Vector Machines....Pages 147-191
Fractals as Pre-Processing Tool for Computational Intelligence Application....Pages 193-212
Unlike traditional computing, Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning.
All the contributors of this volume have direct bearing with this issue. From fundamentals to advanced systems as Multilayer Perceptron Artificial Neural Networks (ANN-MLP), Radial Basis Function Networks (RBF) and its relations with Fuzzy Sets and Support Vector Machines theory; and on to several critical applications in Engineering and Manufacturing. These are among applications where CI has excellent potential.
This volume has specially taken Neural Networks, key elements of CI, to the next level. Both novice and expert readers can benefit from this timely addition to CI based literature. Towards that goal, the editors and the authors have made critical contributions and succeeded. They have paved the road for learning paradigms towards the solution of many real-world problems.
Content:
Front Matter....Pages I-XIII
Soft Computing and its Applications in Engineering and Manufacture....Pages 1-38
Neural Networks Historical Review....Pages 39-65
Artificial Neural Networks....Pages 67-92
Application of Neural Networks....Pages 93-108
Radial Basis Function Networks and their Application in Communication Systems....Pages 109-130
Biological Clues for Up-to-Date Artificial Neurons....Pages 131-146
Support Vector Machines....Pages 147-191
Fractals as Pre-Processing Tool for Computational Intelligence Application....Pages 193-212
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