Multi-attribute Fuzzy Time Series Based on Adaptive Expectation Model

Time-series models have been used to make reasonably accurate predictions in the areas of weather forecasting, academic enrolment and stock price etc...This paper propose a multiple attribute fuzzy time series based on adaptive expectation model, which incorporates trend-weighting and adaptive expectation model into the fuzzy time-series models advanced by Chen´s and Yu ´s method. In verification, using actual trading data of Taiwan Stock Index (TAIEX), we evaluate the accuracy of our approach, and compare our proposed method with Chen´s, Yu´s and Cheng´s methods.