Interpretability of Fuzzy Temporal Models

The paper presents a new approach to assessment of interpretability of fuzzy models. The approach differs from conventional ones, which consider interpretability from the point of structural complexity of both fuzzy model and its elements. In terms of developed approach, the interpretability means the ability of fuzzy model to reflect the same information presented in different forms to different users. Different forms of fuzzy model are given by use of specific inference system, which provides equivalent transformations of fuzzy rules from knowledge base on the linguistic level. In our work, the inference system providing the equivalent transformations of fuzzy rules is developed for the specific class of fuzzy-temporal models. The necessary and sufficient conditions for properties of fuzzy rules are found. Such conditions provide semantic equivalence for equations obtained during fuzzy inference. The formalized criterion is presented for interpretability of fuzzy model. The criterion is based on ability of model to keep information semantics on the fuzzy sets level when it is changed on the linguistic level.