Fuzzy rule based systems (FRBSs) is a rule-based system which uses linguistic
fuzzy variables as antecedents and consequent to represent human understandable
knowledge. They have been applied to various applications and areas throughout
the soft computing literature. However, FRBSs suffers from many drawbacks such
as uncertainty representation, high number of rules, interpretability loss,
high computational time for learning etc. To overcome these issues with FRBSs,
there exists many extensions of FRBSs. This paper presents an overview and
literature review of recent trends on various types and prominent areas of
fuzzy systems (FRBSs) namely genetic fuzzy system (GFS), hierarchical fuzzy
system (HFS), neuro fuzzy system (NFS), evolving fuzzy system (eFS), FRBSs for
big data, FRBSs for imbalanced data, interpretability in FRBSs and FRBSs which
use cluster centroids as fuzzy rules. The review is for years 2010-2021. This
paper also highlights important contributions, publication statistics and
current trends in the field. The paper also addresses several open research
areas which need further attention from the FRBSs research community.Comment: 49 pages, Accepted for publication in ijf