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Intelligent Computing

International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August 16-19, 2006, Proceedings, Part I

  • Conference proceedings
  • © 2006

Overview

Editors:
  1. De-Shuang Huang

    1. Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, China

  2. Kang Li

    1. Carnegie Mellon University,  

  3. George William Irwin

    1. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, UK

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4113)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: ICIC 2006.

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About this book

The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum with dedication to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring together researchers and practitioners from both the academia and industry to share ideas, problems and solutions related to the multifaceted aspects of intelligent computing. The ICIC 2006 to be held in Kunming, Yunnan, China, 16-19 August 2006 is the second International Conference on Intelligent Computing, which is built upon the success of ICIC 2005 held in Hefei, China, 2005. This year, the conference mainly concentrates on the theories & methodologies as well as the emerging applications of intelligent computing. It intends to unify the contemporary intelligent computing techniques within an integral framework that highlights the trends in advanced computational intelligence and bridges the theoretical research with the applications. In particular, the bio-inspired computing emerges as a key role in pursuing for novel technology in recently years. The resulting techniques vitalize the life science engineering and daily life applications. In light of this trend, the theme for this conference is the Emerging Intelligent Computing Technology and Applications. Papers related to this theme were especially solicited, including theories, methodologies, and applications in science and technology.

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Table of contents (166 papers)

  1. Front Matter

    Download chapter PDF

  2. Neural Networks

    1. A Balanced Learning CMAC Neural Networks Model and Its Application to Identification

      • Daqi Zhu, Qingbin Sang
      Pages 1-11

    2. A Cooperative Evolutionary System for Designing Neural Networks

      • Ben Niu, Yunlong Zhu, Kunyuan Hu, Sufen Li, Xiaoxian He
      Pages 12-21

    3. A Neural Network Approach to Medical Image Segmentation and Three-Dimensional Reconstruction

      • Vitoantonio Bevilacqua, Giuseppe Mastronardi, Mario Marinelli
      Pages 22-31

    4. A Neural Network with Finite-Time Convergence for a Class of Variational Inequalities

      • Xing-Bao Gao, Li-Li Du
      Pages 32-41

    5. A Novel Multi-class Support Vector Machine Based on Fuzzy Theories

      • Yong Zhang, Zhongxian Chi, Yu Sun
      Pages 42-50

    6. Chaotic Neural Network with Initial Value Reassigned and Its Application

      • Haipeng Ren, Lingjuan Chen, Fucai Qian, Chongzhao Han
      Pages 51-62

    7. Chaotic Synchronization of Hindmarsh-Rose Neural Networks Using Special Feedback Function

      • HongJie Yu, JianHua Peng
      Pages 63-72

    8. A Comparative Study on Improved Fuzzy Support Vector Machines and Levenberg-Marquardt-Based BP Network

      • Chao-feng Li, Lei Xu, Shi-tong Wang
      Pages 73-82

    9. Comparative Study on Input-Expansion-Based Improved General Regression Neural Network and Levenberg-Marquardt BP Network

      • Chao-feng Li, Jun-ben Zhang, Shi-tong Wang
      Pages 83-93

    10. Deterministic Convergence of an Online Gradient Method with Momentum

      • Naimin Zhang
      Pages 94-105

    11. Fast Kernel Classifier Construction Using Orthogonal Forward Selection to Minimise Leave-One-Out Misclassification Rate

      • X. Hong, S. Chen, C. J. Harris
      Pages 106-114

    12. Gauss-Morlet-Sigmoid Chaotic Neural Networks

      • Yao-qun Xu, Ming Sun
      Pages 115-125

    13. Hidden Markov Models for Recognition Using Artificial Neural Networks

      • V. Bevilacqua, G. Mastronardi, A. Pedone, G. Romanazzi, D. Daleno
      Pages 126-134

    14. Improved Principal Component Analysis and Neural Network Ensemble Based Economic Forecasting

      • Jian Lin, Bangzhu Zhu
      Pages 135-145

    15. Improving the Combination Module with a Neural Network

      • Carlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo
      Pages 146-155

    16. Improving the Intelligent Prediction Model for Macro-economy

      • Jianbo Fan, Lidan Shou, Jinxiang Dong
      Pages 156-167

    17. Integrated Structure and Parameter Selection for Eng-genes Neural Models

      • Patrick Connally, Kang Li, George W. Irwin
      Pages 168-177

    18. Meta-Learning Evolutionary Artificial Neural Networks Using Cellular Configurations: Experimental Works

      • Asma Abu Salah, Yahya Al-Salqan
      Pages 178-193

    19. Modeling Based on SOFM and the Dynamic ε-SVM for Fermentation Process

      • Xuejin Gao, Pu Wang, Chongzheng Sun, Jianqiang Yi, Yating Zhang, Huiqing Zhang
      Pages 194-203
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Other volumes

  1. Intelligent Computing

  2. Computational Intelligence

  3. Computational Intelligence and Bioinformatics

Editors and Affiliations

  • Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, China

    De-Shuang Huang

  • Carnegie Mellon University,  

    Kang Li

  • School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, UK

    George William Irwin

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