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Application of Fuzzy Neural Network for Real Estate Prediction

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3973))

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Abstract

A FNN prediction model based on hedonic price theory to estimate the appropriate price level for a new real estate is proposed. The model includes a database storing hedonic characteristics and coefficients affecting the real estate price level from recently sold projects that are representative in the local environment. The experimental result shows that the fuzzy neural network prediction model has strong function approximation ability and is suitable for real estate price prediction depending on the quality of the available data.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Chongqing Technology and Business University, 400067, Chongqing, China

    Jian-Guo Liu & Xiao-Li Zhang

  2. Department of Foreign Languages, Chongqing Technology and Business University, 400067, Chongqing, China

    Wei-Ping Wu

Authors
  1. Jian-Guo Liu
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  2. Xiao-Li Zhang
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  3. Wei-Ping Wu
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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. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd, 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Liu, JG., Zhang, XL., Wu, WP. (2006). Application of Fuzzy Neural Network for Real Estate Prediction. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_173

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  • DOI: https://doi.org/10.1007/11760191_173

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34482-7

  • Online ISBN: 978-3-540-34483-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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