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Intuitionistic Fuzzy Time Series Forecasting Model Based on Intuitionistic Fuzzy Reasoning

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  • Ya’nan Wang
  • Yingjie Lei
  • Xiaoshi Fan
  • Yi Wang

Abstract

Fuzzy sets theory cannot describe the data comprehensively, which has greatly limited the objectivity of fuzzy time series in uncertain data forecasting. In this regard, an intuitionistic fuzzy time series forecasting model is built. In the new model, a fuzzy clustering algorithm is used to divide the universe of discourse into unequal intervals, and a more objective technique for ascertaining the membership function and nonmembership function of the intuitionistic fuzzy set is proposed. On these bases, forecast rules based on intuitionistic fuzzy approximate reasoning are established. At last, contrast experiments on the enrollments of the University of Alabama and the Taiwan Stock Exchange Capitalization Weighted Stock Index are carried out. The results show that the new model has a clear advantage of improving the forecast accuracy.

Suggested Citation

  • Ya’nan Wang & Yingjie Lei & Xiaoshi Fan & Yi Wang, 2016. "Intuitionistic Fuzzy Time Series Forecasting Model Based on Intuitionistic Fuzzy Reasoning," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-12, January.
    • Handle: RePEc:hin:jnlmpe:5035160
    DOI: 10.1155/2016/5035160
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