Experimental Results for Information Systems Based on Accesses Locality via Intuitionistic Fuzzy Metrics

ABSTRACT

The notion of an intuitionistic fuzzy metric space is a natural generalization of the fuzzy metric space concept which provides mechanisms to measure the degree of nearness and remoteness between two elements of a fuzzy set according to a parameter t. In this work we show how, interpreting t as a value representing the evolution time of an information system, we can use effective prediction tools in systems that show a strong locality component and where operations require the coordination of actions over the set of elements.

Furthermore we show how we can tune the fuzzy metric results in order to predict access histories working on variations of the fuzzy constructions. To this end we study the suitability of a set of continuous t-norms and t-conorms to build fuzzy constructions. We have evaluated the metrics suitability according to their computation time and to the sensitiveness for different representative cases.