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Application of Neural Network to Interactive Physical Programming

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3496))

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Abstract

A neural network based interactive physical programming approach is proposed in this paper. The approximate model of Pareto surface at a given Pareto design is developed based on neural networks, and a map from Pareto designs to their corresponding evaluation values is built. Genetic algorithms is used to find the Pareto design that best satisfies the designer’s local preferences. An example is given to illustrate the proposed method.

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Author information

Authors and Affiliations

  1. School of Mechatronics Engn., University of Electronic Science and Technology of China, Chengdu, Sichuan, 610054, China

    Hongzhong Huang

  2. Department of Mechanical Engineering, University of Alberta, Edmonton, Alberta, T6G 2G8, Canada

    Zhigang Tian

Authors
  1. Hongzhong Huang
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  2. Zhigang Tian
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiaofeng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Huang, H., Tian, Z. (2005). Application of Neural Network to Interactive Physical Programming. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_116

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  • DOI: https://doi.org/10.1007/11427391_116

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25912-1

  • Online ISBN: 978-3-540-32065-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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