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A New Approach to Multi-variable Fuzzy Forecasting Using Picture Fuzzy Clustering and Picture Fuzzy Rule Interpolation Method

  • Pham Huy ThongEmail author
  • Le Hoang Son
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 326)

Abstract

In this paper, a new approach to multi-variable fuzzy forecasting using picture fuzzy clustering and picture fuzzy rule interpolation techniques is proposed. Firstly, we partition dataset into clusters using picture fuzzy clustering algorithm. Secondly, we construct picture fuzzy rules based on given clusters. Finally, we determine the predicted outputs based on the picture fuzzy rule interpolation scheme. Our proposed approach is applied to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) data. The experimental results indicate that our method predicts better forecasting results than some relevant ones.

Keywords

Fuzzy forecasting Picture Fuzzy rule interpolation method Multivariable fuzzy forecasting Picture fuzzy clustering Stock prediction 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.VNU University of Science, Vietnam National UniversityHanoiVietnam

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