The clustering algorithm has membership and nonmembership degrees as intervals.
Arindam Chaudhuri 2015, 'Intuitionistic Fuzzy Possibilistic C Means Clustering Algorithms', Advances in Fuzzy Systemshttp://dx.doi.org/10.1155/2015/238237. Retrieved from DOAJ CC BY 4.0 (https://creativecommons.org/licenses/by-sa/4.0/legalcode)
Then the membership information content and nonmembership information content are obtained based on the basic ideal of axiomatic design principles.
Ming Li 2013, 'Extension of Axiomatic Design Principles for Multicriteria Decision Making Problemsin Intuitionistic Fuzzy Environment', Mathematical Problems in Engineeringhttp://dx.doi.org/10.1155/2013/813471. Retrieved from DOAJ CC BY 4.0 (https://creativecommons.org/licenses/by-sa/4.0/legalcode)
Second, the results are obtained by the interaction between the membership degree interval and the nonmembership degree interval.
Dejian Yu 2014, 'Hydrogen Production Technologies Evaluation Based on Interval-Valued IntuitionisticFuzzy Multiattribute Decision Making Method', Journal of Applied Mathematicshttp://dx.doi.org/10.1155/2014/751249. Retrieved from DOAJ CC BY 4.0 (https://creativecommons.org/licenses/by-sa/4.0/legalcode)