Abstrato

Model for evaluating the quality for distance education based on the intelligent computing with intuitionistic fuzzy information

Xie Yong

In this paper, we investigate the multiple attribute decision making problems for evaluating the quality of Distance education based on the intelligent computing with intuitionistic fuzzy information. We utilize the intuitionistic fuzzy Einstein weighted average (IFEWA) operator to aggregate the intuitionistic fuzzy information corresponding to each alternative and get the overall value of the alternatives, then rank the alternatives and select the most desirable one (s) according to the score function and accuracy function. Finally, an illustrative example for evaluating the quality of Distance education based on the intelligent computing with intuitionistic fuzzy information is given.