The rough and fuzzy set approaches presented here open up many new frontiers for
continued research and development Computational Intelligence and Feature Selection …

The advancements in the domain of Internet of Things (IoT) accelerated the development of
new communication technologies. Machine to machine communication in IoT is …

Fuzzy rule interpolation (FRI) offers an effective approach for making inference possible in
sparse rule-based systems (and also for reducing the complexity of fuzzy models). However …

Many search strategies have been exploited for the task of feature selection (FS), in an effort
to identify more compact and better quality subsets. Such work typically involves the use of …

Fuzzy interpolation does not only help to reduce the complexity of fuzzy models, but also
makes inference in sparse rule-based systems possible. It has been successfully applied to …

Approximate reasoning systems facilitate fuzzy inference through activating fuzzy if–then
rules in which attribute values are imprecisely described. Fuzzy rule interpolation (FRI) …

In this paper, we present a new weighted fuzzy interpolative reasoning method for sparse
fuzzy rule-based systems. The proposed method uses weighted increment transformation …

As a substantial extension to fuzzy rule interpolation that works based on two neighboring
rules flanking an observation, adaptive fuzzy rule interpolation is able to restore system …

In this paper, we present a new method for fuzzy rules interpolation for sparse fuzzy rule-
based systems based on interval type-2 Gaussian fuzzy sets and genetic algorithms. First …

A rule base covering the entire input domain is required for the conventional Mamdani
inference and Takagi–Sugeno–Kang (TSK) inference. Fuzzy interpolation enhances …