TY - JOUR
T1 - Interval data fusion with preference aggregation
AU - Muravyov, Sergey V.
AU - Khudonogova, Liudmila I.
AU - Emelyanova, Ekaterina Y.
N1 - Funding Information:
This work was supported in part by the Ministry of Education and Science of Russian Federation , basic part of the state task “Science”, project 2.5760.2017/8.9 . The senior author was also partly supported by the Tomsk Polytechnic University Competitiveness Enhancement Program grant, projects VIU- NRiI-23/2016 and VIU-IK-110/2017 .
Publisher Copyright:
© 2017 Elsevier Ltd
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/2
Y1 - 2018/2
N2 - It is proposed in the paper the interval data fusion procedure intended for determination of an interval to be consistent with maximal number of given initial intervals (not necessary consistent among each other) and to be with maximal likelihood including a value x∗ that can serve as representative of all the given intervals. An algorithm of the interval fusion with preference aggregation (IF&PA) is proposed and discussed that can be carried out with help of representation of intervals on the real line by weak order relations (or rankings) over a 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. It is considered a space of weak orders induced by the intervals, its properties and dimension. A reasonable number choice problem of discrete values, representing the interval data, is investigated. Related to the problem, computing experiment results and recommendations are given. The interval data fusion procedures can be widely applied in interlaboratory comparisons, prediction of fundamental constant values on the base of different measured values, conformity testing, enhancement of multisensor readings accuracy in sensor networks, etc.
AB - It is proposed in the paper the interval data fusion procedure intended for determination of an interval to be consistent with maximal number of given initial intervals (not necessary consistent among each other) and to be with maximal likelihood including a value x∗ that can serve as representative of all the given intervals. An algorithm of the interval fusion with preference aggregation (IF&PA) is proposed and discussed that can be carried out with help of representation of intervals on the real line by weak order relations (or rankings) over a 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. It is considered a space of weak orders induced by the intervals, its properties and dimension. A reasonable number choice problem of discrete values, representing the interval data, is investigated. Related to the problem, computing experiment results and recommendations are given. The interval data fusion procedures can be widely applied in interlaboratory comparisons, prediction of fundamental constant values on the base of different measured values, conformity testing, enhancement of multisensor readings accuracy in sensor networks, etc.
KW - Comparisons
KW - Data fusion
KW - Interval data processing
KW - Kemeny ranking problem
KW - Monte Carlo simulation
KW - Preferences
KW - Rank aggregation
KW - Robustness
KW - Ties
KW - Triangle numbers
KW - Weak orders
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U2 - 10.1016/j.measurement.2017.08.045
DO - 10.1016/j.measurement.2017.08.045
M3 - Article
AN - SCOPUS:85032201739
VL - 116
SP - 621
EP - 630
JO - Industrial Metrology
JF - Industrial Metrology
SN - 1536-6367
ER -