Monthly Average Wind Speed Forecasting in Giresun Province with Fuzzy Regression Functions Approach

Abstract

In recent years, fuzzy inference systems have been used as an effective method for forecasting problems instead of classical time series methods. Fuzzy inference systems are based on fuzzy sets and use membership values as well as the original data. The fuzzy regression functions approach, which is one of the popular fuzzy inference systems, has different importance from many fuzzy inference systems with its features that it does not have a rule base and is easier to apply, unlike many fuzzy inference systems in the literature. In this study, both the monthly average wind speed forecasting of Giresun Province is performed for the first time in the literature and the fuzzy regression functions approach method is used for the first time in the literature for wind speed forecasting. To evaluate the performance of the fuzzy regression functions approach used to forecast monthly average wind speed in Giresun Province, the results obtained from many methods suggested in the literature for forecasting problems are compared. As a result of the evaluations, it is concluded that the forecasts obtained by the fuzzy regression functions approach are superior than some other methods in the literature.