[01] Nghiem Van Tinh, Faculty of Electronics, Thai Nguyen University of Technology, Thai Nguyen University, Thai Nguyen, Viet Nam.

Fuzzy time series (FTS) models have been proposed to model time series data and have been extended to model numerical data in solving nonlinear and complexity problems. Many factors are believed to affect forecasting accuracy of FTS model. The design of forecasting rules and the lengths of intervals for observations are considered two of them. Therefore, how to cover both issues simultaneously is important for the improvement of forecasting results. In this paper, the development of forecasting model using the harmony search algorithm and fuzzy time series is introduced. Firstly, a forecasting model is constructed from the fuzzy logical relationship and calculate forecasting output by new defuzzification rule. Following, the harmony search algorithm is combined with FTS model to adjust the lengths of each interval and find optimal interval in the universe of discourse with a design to increase forecasting accuracy. In the part of empirical analysis, numerical dataset of Gas online price of Viet Nam is utilized to illustrate the forecasting process and numbers of enrolment of Alabama University is used to compare between proposed model and it's several counterparts. The application results accentuate the superiority of the proposed model compared to the other models based on high -order FTS.

Forecasting, Fuzzy Time Series, Harmony Search, Enrolments, Gas Online Price

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