Fuzzy Granularity in the Knowledge-based Dynamic Fuzzy Sets
Rolly Intan, Siana Halim, Lily Puspa Dewi · Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence · 2018
In 2002, Intan and Mukaidono proposed Knowledge-based Fuzzy Sets (KFS) as an extended concept of the fuzzy set. Here, the membership function of a fuzzy set is subjectively determined by the knowledge. Wang et al. (1988) generalized the concept of fuzzy set, called Dynamic Fuzzy Sets (DFS). In the DFS, the membership degree of an element might dynamically change according to the time's variable. Both extended concepts of fuzzy sets were then combined by Intan et al. to be a hybrid concept, called Knowledge-based Dynamic Fuzzy Set. The concept is regarded as a more generalization of fuzzy sets by considering that the membership function of a given fuzzy set provided by a certain knowledge may be dynamically changed over time as usually happened in the real-world application. To continually extend the concept of knowledge-based dynamic fuzzy sets, this paper discusses how the fuzzy granularity is constructed in the knowledge-based dynamic fuzzy sets. The concepts of objectivity and consistency are discussed, along with their proposed measures.