Temperature prediction using fuzzy time series

نویسندگان

  • Shyi-Ming Chen
  • Jeng-Ren Hwang
چکیده

A drawback of traditional forecasting methods is that they can not deal with forecasting problems in which the historical data are represented by linguistic values. Using fuzzy time series to deal with forecasting problems can overcome this drawback. In this paper, we propose a new fuzzy time series model called the two-factors time-variant fuzzy time series model to deal with forecasting problems. Based on the proposed model, we develop two algorithms for temperature prediction. Both algorithms have the advantage of obtaining good forecasting results.

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عنوان ژورنال:
  • IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society

دوره 30 2  شماره 

صفحات  -

تاریخ انتشار 2000