Variable precision fuzzy rough sets model in the analysis of process data

  • Authors:

  • Alicja Mieszkowicz-Rolka;Leszek Rolka

  • Affiliations:

  • Department of Avionics and Control, Rzeszów University of Technology, Rzeszów, Poland;Department of Avionics and Control, Rzeszów University of Technology, Rzeszów, Poland

  • Venue:
  • RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper is concerned with describing and analyzing the control actions which are accomplished by a human operator, who controls a complex dynamic system. The decision model is expressed by means of a decision table with fuzzy attributes. Decision tables are generated by the fuzzification of crisp data, basing on a set of fuzzy linguistic values of the attributes. A T-similarity relation is chosen for comparing the elements of the universe. Fuzzy partitions of the universe with respect to condition and decision attributes are generated. The task of stabilization of the aircraft's altitude performed by a pilot is considered as an illustrative example. The limit-based and mean-based variable precision fuzzy rough approximations are determined. The measure of u-approximation quality is used for evaluating the consistency of the human operator's decision model, and assessing the importance of particular condition attributes in the control process.