Information in real life may have linguistically vagueness. Thus, type-1 fuzzy set was introduced to model this uncertainty. Additionally, same words will mean variously to different people, which means uncertainty also exists when associated with the membership function of a type-1 fuzzy set. Type-2 fuzzy set is then invented to express the hybrid uncertainty of both primary fuzziness and secondary one of membership functions. On the one hand, type-2 fuzzy variable models the vagueness of information better. On the other hand, those variables are hard to deal with its three-dimensional feature given. To address problems in presence of such variables with hybrid fuzziness, a new class of type-2 fuzzy regression model is built based on credibility theory, and is called the T2 fuzzy expected value regression model. The new model will be developed into two forms: form-A and form-B. This paper is a further work based on our former research of type-2 fuzzy qualitative regression model.
|ホスト出版物のタイトル||IEEE International Conference on Fuzzy Systems|
|出版ステータス||Published - 2013|
|イベント||2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013 - Hyderabad|
継続期間: 2013 7月 7 → 2013 7月 10
|Other||2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013|
|Period||13/7/7 → 13/7/10|
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