A weighted fuzzy time series model based on adoptive OWA operators

Since Song and Chissom proposed the fuzzy time series in 1993, many previous studies have proposed variant fuzzy time series models to deal with uncertain and vague data. A drawback of these models is that they do not consider appropriately the weights of fuzzy relations. This paper proposes an adoptive fuzzy time series model to solve above problems. It develops weighted fuzzy rules by calculating the count of each fuzzy relation and an adoptive weighting process is executed according to the ordered weighted averaging operators. The yearly data on enrollments at the University of Alabama are adopted to verify and evaluate the performance of the proposed model.