Fuzzy Treatment of Candidate Outliers in Measurements | Zendy

Giampaolo E. D’Errico | Zendy; Nadir Murru | Zendy

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Fuzzy Treatment of Candidate Outliers in Measurements

Author(s) -

Giampaolo E. D’Errico,

Nadir Murru

Publication year - 2012

Publication title -

advances in fuzzy systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.38

H-Index - 19

eISSN - 1687-711X

pISSN - 1687-7101

DOI - 10.1155/2012/783843

Subject(s) - outlier , fuzzy logic , robustness (evolution) , data mining , probabilistic logic , computer science , metrology , context (archaeology) , artificial intelligence , statistical hypothesis testing , fuzzy set , robust statistics , machine learning , statistics , mathematics , geography , biochemistry , chemistry , archaeology , gene

Robustness against the possible occurrence of outlying observations is critical to the performance of a measurement process. Open questions relevant to statistical testing for candidate outliers are reviewed. A novel fuzzy logic approach is developed and exemplified in a metrology context. A simulation procedure is presented and discussed by comparing fuzzy versus probabilistic models

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