Title :
Automated diagnostic system using graph clustering algorithm and fuzzy logic method
Author_Institution :
Dept. of Inf., Warsaw Agric. Univ., Warsaw
Abstract :
The paper presents the method of the automated diagnostic system generation using fuzzy logic supported by the graph clustering algorithm. Algorithm of the learning data processing using self-organization method and fuzzy logic module generation are presented. Application of the method for the diagnostics of the analog system (DC motor) is presented and its advantages and disadvantages are considered. Conclusions and future prospects are included.
Keywords :
fuzzy set theory; graph theory; learning (artificial intelligence); pattern clustering; DC motor; analog system; automated diagnostic system generation; fuzzy logic module generation; graph clustering algorithm; learning data processing; self-organization method; Clustering algorithms; DC motors; Data mining; Data processing; Decision trees; Fuzzy logic; Informatics; Machine learning; Machine learning algorithms; System testing;
Conference_Titel :
Circuit Theory and Design, 2007. ECCTD 2007. 18th European Conference on
Conference_Location :
Seville
Print_ISBN :
978-1-4244-1341-6
Electronic_ISBN :
978-1-4244-1342-3
DOI :
10.1109/ECCTD.2007.4529712
