The hybridization of rough sets and fuzzy sets has focused on creating an end product that extends both contributing computing paradigms in a conservative way. As a result, the hybrid theory inherits their respective strengths, but also exhibits some weaknesses. In particular, although they allow for gradual membership, fuzzy rough sets are still abrupt in a sense that adding or omitting a sing...

In this article, a new hybrid model named linear Diophantine fuzzy rough set (LDFRS) is proposed to magnify the notion of (RS) and (LDFS). Concerning LDFRS, it more efficient discuss fuzziness roughness in terms approximation spaces (LDFA spaces); plays vital role information analysis, data computational intelligence. The concept (<p,p?>,<q,q?>)-indiscernibility relation (LDF relati...

The aim of this paper is to introduce $(L,M)$-fuzzy closurestructure where $L$ and $M$ are strictly two-sided, commutativequantales. Firstly, we define $(L,M)$-fuzzy closure spaces and getsome relations between $(L,M)$-double fuzzy topological spaces and$(L,M)$-fuzzy closure spaces. Then, we introduce initial$(L,M)$-fuzzy closure structures and we prove that the category$(L,M)$-{bf FC} of $(L,M...

The main objective of this special issue is to present readers with the significantly extended and improved versions of the articles presented at the International Conference on Rough Sets, Fuzzy Sets, and Granular Computing (RSFDGrC’05) held in Regina, Canada in September 2005. In the standard rough set model, the lower and upper approximations are defined based on the two extreme cases (full ...

in this work, we define a fuzzy soft set theory and its related properties. we then define fuzzy soft aggregation operator that allows constructing more efficient decision making method. finally, we give an example which shows that the method can be successfully applied to many problems that contain uncertainties.