A graph clustering-based method of the assessment of rough sets efficiency in the diagnostics of analog systems

摘要

The paper presents the method of analyzing the rough-sets based diagnostic module using the graph clustering algorithm. The former is used to extract knowledge from the learning data set and use it to process the testing data set. The latter is used to find dependencies in sets that make diagnostic process difficult. This way the information about the structure of the set influencing diagnostic efficiency is obtained. Both algorithms are tested on the example of the electronic circuit - the fifth order lowpass Butterworth filter. Analysis of the algorithms efficiency is performed and remarks for the future applications presented.