Fuzzy-operators weight refinements

The advantages of intelligent technologies, and fuzzy logic as a leading methodology among them, lead to increasing popularity in various systems of control, approximate reasoning, optimization and ranking, managing uncertainty, prediction, etc. All these applications consider combination operations, i.e., fuzzy sets aggregation. Most frequently used Zadeh's operators of intersection and union appear to be very rough in certain applications. Therefore a need for modification and refinement of their functionality arose. The selection of the compensatory operator itself, as well as his parameter, has to be done after a thorough problem analysis. The proposed analysis is applicable to any problem that considers specific aggregation of fuzzy sets, depending on problems and systems depicted by qualitative attributes. Some of those problems arise in various fuzzy rules aggregating methods while fuzzy inferencing, in multiple criteria optimization, in the problem of fuzzy number rankings, where the modification of the connection's weight results in more precise and correct system depiction, and also as in data representation problem. The results are graphically presented and discussed in context of adequate possible applications. A test example exposed in this paper emphasizes an interesting application of data representation by the fuzzy logic function, where a selection of fuzzy-operator has an important part of the function modeling procedure.