A fuzzy logic-based method for outliers detection

Authors:
S. Cateni;V. Colla;M. Vannucci
Affiliations:
PERCRO Lab, Scuola Superiore S.Anna, Pontedera, PI, Italy;PERCRO Lab, Scuola Superiore S.Anna, Pontedera, PI, Italy;PERCRO Lab, Scuola Superiore S.Anna, Pontedera, PI, Italy
Venue:
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Year:
2007

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Abstract

The paper presents a method based on a fuzzy inference system that is capable of pointing out outliers in a series of data. The proposed algorithm has been adopted in order to process data coming from a real industrial context. The overall purpose of the work is to point out anomalous data due to several causes such as erroneous measurements, errors made by the operator that filled the database or anomalous process conditions. A standard statistical technique for outlier detection as been exploied for the same purpose: the performance obtained by the two methods are compared and discussed.