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) …

IoT devices are notoriously vulnerable even to trivial attacks and can be easily
compromised. In addition, resource constraints and heterogeneity of IoT devices make it …

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 …

In this paper, we present a new method for multi-variable fuzzy forecasting based on fuzzy
clustering and fuzzy rule interpolation techniques. First, the proposed method constructs …

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 …

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

Network intrusion is a growing threat with potentially severe impacts, which can be
damaging in multiple ways to network infrastructures and digital/intellectual assets in the …