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

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

Introduces a singular value-based method for reducing a given fuzzy rule set. The method
conducts singular value decomposition of the rule consequents and generates certain linear …

The concept of fuzzy rule interpolation in sparse rule bases was introduced in 1993. It has
become a widely researched topic in recent years because of its unique merits in the topic of …

Interpolative reasoning does not only help reduce the complexity of fuzzy models but also
makes inference in sparse rule-based systems possible. This paper presents an …

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 …

The first published result in fuzzy rule interpolation was the/spl alpha/-cut based fuzzy rule
interpolation, termed as KH fuzzy rule interpolation, originally devoted for complexity …

Fuzzy rule based systems have been very popular in many engineering applications.
However, when generating fuzzy rules from the available information, this may result in a …

Treatments of patients with hypertension can be done in two ways, namely modifying
lifestyle and antihypertensive drugs. Generally giving hypertensive drugs depends on age …

This paper introduces a new approach for fuzzy interpolation and extrapolation of sparse
rule base comprising of membership functions with finite number of characteristic points. The …