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

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 …

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 …

Fuzzy interpolative reasoning is an inference technique for dealing with the sparse rules
problem in sparse fuzzy-rule-based systems. In this paper, we present a new fuzzy …

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 …

In this paper, we propose a weighted fuzzy interpolative reasoning method for sparse fuzzy
rule-based systems. It is based on a genetic algorithm (GA)-based weight-learning …

Fuzzy interpolative reasoning strengthens the power of fuzzy inference by the enhancement
of the robustness of fuzzy systems and the reduction of the systems' complexity. However …

This paper presents a new framework for the symbolic representation of data which is
referred to as signatures. The definitions of signatures and of signature trees are first given …