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Soft Computing in Industrial Applications

Recent and Emerging Methods and Techniques

  • Conference proceedings
  • © 2007

Overview

Editors:
  1. Ashraf Saad
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  2. Keshav Dahal
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  3. Muhammad Sarfraz
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  4. Rajkumar Roy
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  • contains a collection of papers that were presented at the 11th On-line World Conference on Soft Computing in Industrial Applications, held in September-October 2006

Part of the book series: Advances in Intelligent and Soft Computing (AINSC, volume 39)

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Table of contents (29 papers)

  1. Front Matter

    Download chapter PDF

  2. Invited Keynote

    1. Hybrid Dynamic Systems in an Industry Design Application

      • Pieter J. Mosterman, Elisabeth M. O’Brien
      Pages 1-16

  3. Part I: Soft Computing in Computer Graphics, Imaging and Vision

    1. Front Matter

      Pages 17-17
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    2. Object Recognition Using Particle Swarm Optimization on Fourier Descriptors

      • Muhammad Sarfraz, Ali Taleb Ali Al-Awami
      Pages 19-29

    3. Gestix: A Doctor-Computer Sterile Gesture Interface for Dynamic Environments

      • Juan Wachs, Helman Stern, Yael Edan, Michael Gillam, Craig Feied, Mark Smith et al.
      Pages 30-39

    4. Differential Evolution for the Registration of Remotely Sensed Images

      • I. De Falco, A. Della Cioppa, D. Maisto, E. Tarantino
      Pages 40-49

    5. Geodesic Distance Based Fuzzy Clustering

      • Balazs Feil, Janos Abonyi
      Pages 50-59

  4. Part II: Control Systems

    1. Front Matter

      Pages 61-61
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    2. Stability Analysis of the Simplest Takagi-Sugeno Fuzzy Control System Using Popov Criterion

      • Xiaojun Ban, X. Z. Gao, Xianlin Huang, Hang Yin
      Pages 63-71

    3. Identification of an Experimental Process by B-Spline Neural Network Using Improved Differential Evolution Training

      • Leandro dos Santos Coelho, Fabio A. Guerra
      Pages 72-81

    4. Applying Particle Swarm Optimization to Adaptive Controller

      • Leandro dos Santos Coelho, Fabio A. Guerra
      Pages 82-91

    5. B-Spline Neural Network Using an Artificial Immune Network Applied to Identification of a Ball-and-Tube Prototype

      • Leandro dos Santos Coelho, Rodrigo Assunção
      Pages 92-101

  5. Part III: Pattern Recognition

    1. Front Matter

      Pages 103-103
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    2. Pattern Recognition for Industrial Security Using the Fuzzy Sugeno Integral and Modular Neural Networks

      • Patricia Melin, Alejandra Mancilla, Miguel Lopez, Daniel Solano, Miguel Soto, Oscar Castillo
      Pages 105-114

    3. Application of a GA/Bayesian Filter-Wrapper Feature Selection Method to Classification of Clinical Depression from Speech Data

      • Juan Torres, Ashraf Saad, Elliot Moore
      Pages 115-121

    4. Comparison of PSO-Based Optimized Feature Computation for Automated Configuration of Multi-sensor Systems

      • Kuncup Iswandy, Andreas Koenig
      Pages 122-131

    5. Evaluation of Objective Features for Classification of Clinical Depression in Speech by Genetic Programming

      • Juan Torres, Ashraf Saad, Elliot Moore
      Pages 132-143

    6. A Computationally Efficient SUPANOVA: Spline Kernel Based Machine Learning Tool

      • Boleslaw K. Szymanski, Lijuan Zhu, Long Han, Mark Embrechts, Alexander Ross, Karsten Sternickel
      Pages 144-155

  6. Part IV: Classification

    1. Front Matter

      Pages 157-157
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    2. Multiobjective Genetic Programming Feature Extraction with Optimized Dimensionality

      • Yang Zhang, Peter I Rockett
      Pages 159-168
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Keywords

About this book

Soft Computing admits approximate reasoning, imprecision, uncertainty and partial truth in order to mimic aspects of the remarkable human capability of making decisions in real-life and ambiguous environments. "Soft Computing in Industrial Applications" contains a collection of papers that were presented at the 11th On-line World Conference on Soft Computing in Industrial Applications, held in September-October 2006. This carefully edited book provides a comprehensive overview of the recent advances in the industrial applications of soft computing and covers a wide range of application areas, including data analysis and data mining, computer graphics, intelligent control, systems, pattern recognition, classifiers, as well as modeling optimization. The book is aimed at researchers and practitioners who are engaged in developing and applying intelligent systems principles to solving real-world problems. It is also suitable as wider reading for science and engineering postgraduate students.

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