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Fuzzy Inference System with Probability Factor and Its Application in Data Mining

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Web Technologies Research and Development - APWeb 2005 (APWeb 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3399))

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Abstract

In the fuzzy inference system, the construction of the fuzzy rule-base is a key issue. In this paper we provide an identification method for fuzzy model by interpreting the importance factor of each fuzzy rule as the conditional probability of the consequent given the premise. One method of computing the conditional probability is presented. We call this fuzzy model as the fuzzy inference system with probability factor (FISP). One learning process of FISP is also presented in this paper. The application of FISP in time series predication manifests that FISP is very effective.

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Author information

Authors and Affiliations

  1. College of Economics, Zhejiang University, Hangzhou, Zhejiang Province, 310027, P.R. China

    Jiacheng Zheng

  2. College of Computer Science, Zhejiang University, Hangzhou, Zhejiang Province, 310027, P.R. China

    Yongchuan Tang

Authors
  1. Jiacheng Zheng
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  2. Yongchuan Tang
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Editor information

Editors and Affiliations

  1. Victoria University, Australia

    Yanchun Zhang

  2. University of Kyoto, Japan

    Katsumi Tanaka

  3. Chinese University of Hong Kong, Hong Kong, China

    Jeffrey Xu Yu

  4. Key Laboratory of Data Engineering and Knowledge Engineering, Renmin University of China, MOE, 100872, Beijing, P.R. China

    Shan Wang

  5. Department of Computer Science and Engineering, Shanghai Jiatong University, 80 Dongcuan Road, 200240, Shanghai, China

    Minglu Li

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© 2005 Springer-Verlag Berlin Heidelberg

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Zheng, J., Tang, Y. (2005). Fuzzy Inference System with Probability Factor and Its Application in Data Mining. In: Zhang, Y., Tanaka, K., Yu, J.X., Wang, S., Li, M. (eds) Web Technologies Research and Development - APWeb 2005. APWeb 2005. Lecture Notes in Computer Science, vol 3399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31849-1_90

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  • DOI: https://doi.org/10.1007/978-3-540-31849-1_90

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25207-8

  • Online ISBN: 978-3-540-31849-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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