MVLSC Home · Issue Contents · Forthcoming PapersInformation Measures on Linear Diophantine Fuzzy
Soft Sets with Their Applications to the Medical Diagnosis
Başak Aldemir, Ebru Aydoğdu, Elif Güner and Halis Aygün
Linear Diophantine fuzzy soft set (LDFSS) is a powerful tool to handle uncertain information more flexibly and comprehensively. The aim of this paper is to propose some information measures (similarity measure, distance measure and entropy) for the LDFSS environment. For this aim, we first redefine the notion of LDFSS from a more general perspective. Then, we extend some well-known classical distances such as Hamming distance, Euclidean distance, Minkowski distance and etc. for the LDFSS environment. Also, we give some similarity measures where some of which are constructed from the presented distance measures and introduce the entropy measure for the LDFSSs. After, we construct two different decision-making methods, one based on the presented similarity measures and the other based on the TOPSIS method with entropy. Finally, we demonstrate a numerical example related to the medical diagnosis to illustrate that the proposed methods are more objective and feasible in the applications.
Keywords: Linear Diophantine fuzzy set, soft set, distance measure, similarity measure, entropy, medical diagnosis, TOPSIS, MCGDM