Representation of interval data by weak orders yields robustness of the data fusion outcomes

Abstract

It is shown in the paper that an interval data fusion procedure can be carried out by means of representation of intervals on the real line by weak order relations (or rankings) over set of discrete values belonging to these intervals. It is possible to determine a consensus ranking for collection of discrete values rankings, corresponding to initial intervals. The highest ranked value, accepted as a result of the fusion, guarantees improved accuracy and robustness of the interval data fusion procedure outputs.

Original language	English
Article number	012064
Journal	Journal of Physics: Conference Series
Volume	772
Issue number	1
DOIs	https://doi.org/10.1088/1742-6596/772/1/012064
Publication status	Published - 12 Dec 2016
Event	2016 Joint IMEKO TC1-TC7-TC13 Symposium: Metrology Across the Sciences: Wishful Thinking? - Berkeley, United States Duration: 3 Aug 2016 → 5 Aug 2016

ASJC Scopus subject areas

Physics and Astronomy(all)

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10.1088/1742-6596/772/1/012064

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title = "Representation of interval data by weak orders yields robustness of the data fusion outcomes",

abstract = "It is shown in the paper that an interval data fusion procedure can be carried out by means of representation of intervals on the real line by weak order relations (or rankings) over set of discrete values belonging to these intervals. It is possible to determine a consensus ranking for collection of discrete values rankings, corresponding to initial intervals. The highest ranked value, accepted as a result of the fusion, guarantees improved accuracy and robustness of the interval data fusion procedure outputs.",

author = "Muravyov, {S. V.} and Khudonogova, {L. I.} and Marinushkina, {I. A.}",

year = "2016",

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AB - It is shown in the paper that an interval data fusion procedure can be carried out by means of representation of intervals on the real line by weak order relations (or rankings) over set of discrete values belonging to these intervals. It is possible to determine a consensus ranking for collection of discrete values rankings, corresponding to initial intervals. The highest ranked value, accepted as a result of the fusion, guarantees improved accuracy and robustness of the interval data fusion procedure outputs.

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