|
|
|
|
| LEADER |
00000naa0a2200000 4500 |
| 001 |
665068 |
| 005 |
20260807071628.0 |
| 035 |
|
|
|a (RuTPU)RU\TPU\network\36267
|
| 035 |
|
|
|a RU\TPU\network\33629
|
| 090 |
|
|
|a 665068
|
| 100 |
|
|
|a 20210802d2020 k y0engy50 ba
|
| 101 |
0 |
|
|a eng
|
| 135 |
|
|
|a drcn ---uucaa
|
| 181 |
|
0 |
|a i
|
| 182 |
|
0 |
|a b
|
| 200 |
1 |
|
|a Precise Measurand Value Estimating by Interval Fusion with Preference Aggregation: Heteroscedasticity Case
|f S. V. Muravyov (Murav’ev), L. I. Khudonogova, Dai Minh Ho
|
| 203 |
|
|
|a Text
|c electronic
|
| 300 |
|
|
|a Title screen
|
| 320 |
|
|
|a [References: 21 tit.]
|
| 330 |
|
|
|a It is considered the problem of determination of a reference value for heteroscedastic interval data. For this aim, the newly proposed by the authors interval fusion with preference aggregation (IF&PA) procedure is used. The procedure, modified to improve the accuracy of the fusion result, is presented and applied to process the heteroscedastic data of a real experiment. The experiment consisted in determination of the reference value of DC voltage based on the readings of five different models of multimeters. For comparison, the same data were processed by the method of weighted mean. For two methods, an absolute deviations of the obtained reference values from the nominal value (which is a high-precision calibrator output) and reference value uncertainties were estimated. It is shown that the IF&PA procedure allows to obtain a reference value very close to nominal value and with considerably reduced uncertainty in comparison with traditional method based on weighted mean calculation.
|
| 463 |
|
|
|t Global trends in Testing, Diagnostics & Inspection for 2030
|o Proceedings 17th IMEKO TC 10 and EUROLAB Virtual Conference, Dubrovnik, October 20-22, 2020
|o 2nd Conference jointly organized by IMEKO and EUROLAB aisbl
|v [P. 208-213]
|d 2020
|
| 610 |
1 |
|
|a электронный ресурс
|
| 610 |
1 |
|
|a труды учёных ТПУ
|
| 610 |
1 |
|
|a interval fusion
|
| 610 |
1 |
|
|a preference aggregation
|
| 610 |
1 |
|
|a heteroscedasticity
|
| 610 |
1 |
|
|a consensus estimate
|
| 610 |
1 |
|
|a ranking
|
| 610 |
1 |
|
|a интервальная сварка
|
| 610 |
1 |
|
|a агрегирование предпочтений
|
| 610 |
1 |
|
|a гетероскедастичность
|
| 610 |
1 |
|
|a рейтинг
|
| 700 |
|
1 |
|a Muravyov (Murav’ev)
|b S. V.
|c specialist in the field of control and measurement equipment
|c Professor of Tomsk Polytechnic University,Doctor of technical sciences
|f 1954-
|g Sergey Vasilyevich
|3 (RuTPU)RU\TPU\pers\31262
|9 15440
|
| 701 |
|
1 |
|a Khudonogova
|b L. I.
|c specialist in the field of informatics and computer technology
|c Associate Professor of Tomsk Polytechnic University, Candidate of Technical Sciences
|f 1989-
|g Ludmila Igorevna
|3 (RuTPU)RU\TPU\pers\32893
|9 16741
|
| 701 |
|
0 |
|a Dai Minh Ho
|c специалист в области автоматического управления
|c инженер-исследователь Томского политехнического университета
|f 1991-
|3 (RuTPU)RU\TPU\pers\43358
|
| 712 |
0 |
2 |
|a Национальный исследовательский Томский политехнический университет
|b Инженерная школа информационных технологий и робототехники
|c 2017-
|x TPU
|7 ca
|8 rus
|9 28330
|
| 801 |
|
2 |
|a RU
|b 63413507
|c 20210802
|g RCR
|
| 856 |
4 |
|
|u https://www.imeko.org/publications/tc10-2020/IMEKO-TC10-2020-029.pdf
|
| 942 |
|
|
|c CF
|