Novel distance, similarity and entropy measures for interval valued intuitionistic fuzzy soft set

Article type: Research Article

Authors: Sonia, ^a | Tiwari, Pratiksha^{b; *} | Gupta, Priti^a

Affiliations: [a] Maharashi Dayananad University, Rohtak, Haryana | [b] Delhi Institute of Advanced Studies, Rohini, Delhi

Correspondence: [*] Corresponding author. Pratiksha Tiwari, Delhi Institute of Advanced Studies, Rohini, Delhi. E-mail: parth12003@yahoo.co.in.

Abstract: Soft and fuzzy sets are generic tools to deal with uncertainty. Both contemporary sets are not suitable to deal with all type of uncertain parameters. In this paper the hybridization of soft with extended fuzzy set information measures are derived. Interval-valued intuitionistic fuzzy soft set theory is a powerful tool for dealing with uncertainty of knowledge in information systems. In this paper, firstly some distance and similarity measures for interval-valued intuitionistic fuzzy soft sets were proposed. Further, some new entropy measures are also introduced by using the similarity measures. The validity of these measures is also proved. Applications of the distance measures is also used in the field of multi attribute decision making and medical diagnosis. The proposed measures are also compared with an existing measure to prove its significance.

Keywords: Interval valued intuitionistic fuzzy soft set (IVIFSS), interval number, hesitant factor, Fuzzy soft set (FSS)

DOI: 10.3233/JIFS-212647

Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3067-3086, 2022