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Research on Coordination Model of Multiplexed System Based on DEA

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Advances in Neural Networks – ISNN 2009 (ISNN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5551))

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Abstract

First, based on the viewpoint of system theory, this paper explained the coordination and its degree’s concept and connotation. Then it introduced the performance of Data Envelopment Analysis (DEA) method and the membership concept of fuzzy mathematics degree, which established the coordination degree evaluation model of multiplexed system, appraised the running status and the tendency of the coordination among the multiplexed system’s essential factors and subsystems. Finally we took an empirical analysis with this model into Chinese Guangxi’s multiplexed system which concludes economy, education and Science Technical between 1994 and 2006. The result indicated: this multiplexed system’s static coordination degree changed in a big way, and the dynamic coordination degree swings nearby 0.92, the multiplexed system development is at a basic coordinated condition.

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Author information

Authors and Affiliations

  1. Institute of Systems Engineering, Huazhong University of Science & Technology, Wuhan, 430074, China

    Zhengping He, Hongtao Zhou, Wei Zeng, Yushuo Chen & Qi Fei

Authors
  1. Zhengping He
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  2. Hongtao Zhou
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  3. Wei Zeng
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  4. Yushuo Chen
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  5. Qi Fei
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, NJ 07030, Hoboken, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, 501 E. St. Joseph Street, Rapid City, SD 57701, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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He, Z., Zhou, H., Zeng, W., Chen, Y., Fei, Q. (2009). Research on Coordination Model of Multiplexed System Based on DEA. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5551. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01507-6_124

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  • DOI: https://doi.org/10.1007/978-3-642-01507-6_124

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01506-9

  • Online ISBN: 978-3-642-01507-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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