Special Aspects of the Design of Fuzzy Inference Mechanism
Tatiana Ledeneva · 2020 2nd International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA) · 2020
Fuzzy systems are the most important class of intelligent information systems. The knowledge base in the form of if-then-rules describes the dependence of the output variable on the input variables. The main component of a fuzzy system is the inference mechanism, which determines the output fuzzy set. It is based on the compositional inference rule. The quality of approximation is determined by the functional representation of those operations that implement the inference algorithm. The article presents the results of a study regarding the selection of triangular norms and conorms, implications, operations and aggregation schemes of if-then-rules. Recommendations have been developed for combining various components. Comprehensive assessments of the quality of implementation of the inference mechanism are proposed.