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Selection of Optimal Technological Innovation Projects Combining Value Engineering with Fuzzy Synthetic Evaluation

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Advances in Machine Learning and Cybernetics

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3930))

Abstract

Value engineering is introduced into a selection of optimal technological innovation projects. The function and cost factors of a project have been analyzed from the viewpoint of the whole enterprise, and new index systems of evaluation on the project are constructed. Since many factors influence the success of a technological innovation project in direct ways or in potential indirect ways, it is difficult to find a common appraisal method to achieve a satisfactory and effective scientific result. Therefore, multistage fuzzy synthetic evaluation is adopted. In addition, this novel method can be programmed to be used in similar fields, so it is of high practicability.

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Author information

Authors and Affiliations

  1. Department of Economy and Management, North China Electric Power University, 071003, Baoding, China

    Yuan-sheng Huang, Jun-hua Zhou & Jian-xun Qi

Authors
  1. Yuan-sheng Huang
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  2. Jun-hua Zhou
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  3. Jian-xun Qi
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Editor information

Editors and Affiliations

  1. Department of Computing, Hong Kong Polytechnic University, P.O. Box, Hong Kong, China

    Daniel S. Yeung

  2. School of Creative Media, City University of Hong Kong,, China

    Zhi-Qiang Liu

  3. Department of Mathematics and Computer Science, Hebei University, 071002, Baoding, Hebei, P.R. China

    Xi-Zhao Wang

  4. School of Electrical and Information Engineering, University of Sydney, 2006, NSW, Australia

    Hong Yan

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© 2006 Springer-Verlag Berlin Heidelberg

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Huang, Ys., Zhou, Jh., Qi, Jx. (2006). Selection of Optimal Technological Innovation Projects Combining Value Engineering with Fuzzy Synthetic Evaluation. In: Yeung, D.S., Liu, ZQ., Wang, XZ., Yan, H. (eds) Advances in Machine Learning and Cybernetics. Lecture Notes in Computer Science(), vol 3930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11739685_42

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  • DOI: https://doi.org/10.1007/11739685_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33584-9

  • Online ISBN: 978-3-540-33585-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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