A complete ranking of incomplete interval information

• Published in: Expert systems with applications Vol. 41; no. 4; pp. 1947 - 1954
• Main Authors: Geetha, Sivaraman, Lakshmana Gomathi Nayagam, V., Ponalagusamy, R.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01-03-2014; Elsevier
• Subjects: Algorithmics. Computability. Computer arithmetics; Applied sciences; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Expert systems; Fuzzy systems; Information system; Information systems; Interval-valued intuitionistic fuzzy numbers; Intervals; Membership and nonmembership score functions; Ranking; Theoretical computing; Vague and precise score functions; Membership and nonmembership score functions; Information system; Interval-valued intuitionistic fuzzy numbers; Vague and precise score functions; Membership function; Hierarchical classification; Set computation; Axiomatic; Fuzzy logic; Uncertain system; Information source; Ordering; Interval matrix; Fuzzy number; Incomplete information; Artificial intelligence; Intelligent system
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2013.08.090

•Axioms for all the intuitions in incomplete interval information (III) are framed.•An axiomatic complete ranking for incomplete interval information is defined.•The significance of the proposed process over existing ranking process is depicted.•An algorithm for decision making from an III system is given.•A numerical illustration is given for better understanding of the proposed model.
The information received from a source, represented by an information system, involves quantitative, qualitative and incomplete information. Such incomplete information are fed into the intelligent system for enhancing accuracy using interval-valued intuitionistic fuzzy numbers (IVIFN). Ranking of IVIFN is an important component of any incomplete interval information system. But existing techniques do not give complete information about alternatives in some cases. In this paper, a new method for complete ranking of incomplete interval information using axiomatic set of membership, non membership, vague and precise score functions to IVIFN is proposed and compared with existing techniques using an illustrative example.