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In recent years, many fuzzy time series models have already been used to solve nonlinear and complexity issues. However, first-order fuzzy time series models have proven to be insufficient for solving these problems. For this reason, many researchers have been proposed high-order fuzzy time series model to improve the forecasting accuracy. From this viewpoint. This paper presents a high-order forecasting model based on fuzzy time series (FTS) and harmony search algorithm to overcome thedoi:10.5281/zenodo.2554014 fatcat:l2wk5bo54fdc3liatzd7ot2ss4