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Grey Compertz Prediction Model Based on Hybrid Differential Evolution Algorithm

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Emerging Research in Artificial Intelligence and Computational Intelligence (AICI 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 315))

Abstract

Aiming at the educational investment scheduling that is a complex hard combinatorial problem between education and economy, an effective algorithm based on differential evolution is proposed by using a special investing scheme and combining DE based evolutionary search and local search, the exploration and exploitation abilities are enhanced and well balanced for solving the educational problems. The compertz model is established to predict the family education investment in 2008. After this, the government education investment in 2008 can be got through minimum education investment structure. Simulation results demonstrate the proposed algorithm is effective.

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Author information

Authors and Affiliations

  1. Department of Basic Teaching, Air Force Logistic Academy, Jiangsu, Xuzhou, 221002, China

    Wei Zhang, Guoliang He & Lifang Kong

Authors
  1. Wei Zhang
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  2. Guoliang He
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  3. Lifang Kong
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Editor information

Editors and Affiliations

  1. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  2. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

  3. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, Victoria, Australia

    Hepu Deng

  4. School of Electronics and Information, Tongji University, China, 201804, Shanghai, China

    Duoqian Miao

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© 2012 Springer-Verlag Berlin Heidelberg

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Zhang, W., He, G., Kong, L. (2012). Grey Compertz Prediction Model Based on Hybrid Differential Evolution Algorithm. In: Lei, J., Wang, F.L., Deng, H., Miao, D. (eds) Emerging Research in Artificial Intelligence and Computational Intelligence. AICI 2012. Communications in Computer and Information Science, vol 315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34240-0_5

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  • DOI: https://doi.org/10.1007/978-3-642-34240-0_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34239-4

  • Online ISBN: 978-3-642-34240-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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