Abstract:

The objectivity of the fuzzy time series (FTS) forecasting theory in description of uncertain data sets is limited by the fuzzy sets theory. To break this limitation, an intuitionistic FTS (IFTS) forecasting model is built. Firstly, the fuzzy clustering algorithm is used to get unequal domaindividing intervals. And then a more objective construction method of membership and non-membership functions of intuitionistic fuzzy sets (IFS) is proposed. Thirdly, forecasting rules based on intuitionistic fuzzy approximate reasoning are given. Finally, experiments on datasets of enrollments of the university of Alabama and the total retail sales of social consumer goods of China are carried out which show that the new model improves the prediction accuracy with its validity and superiority.