Adjustment of fundamental physical constant values using the interval fusion with preference aggregation

For adjustment of fundamental constants, the interval fusion with preference aggregation (IF&PA) method is proposed to be used, which was proved to be robust and accurate when processing heteroscedastic data. The method forms a profile of rankings of discrete values obtained by partition of the...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Muravyov, Sergey V. [verfasserIn] Khudonogova, Liudmila I. [verfasserIn] Ho, Minh Dai [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Interval fusion Preference aggregation Fundamental constant adjustment Consensus estimate Ranking

Übergeordnetes Werk:	Enthalten in: Measurement - Amsterdam [u.a.] : Elsevier Science, 1983, 163
Übergeordnetes Werk:	volume:163

DOI / URN:	10.1016/j.measurement.2020.108037

Katalog-ID:	ELV004687620

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520			\|a For adjustment of fundamental constants, the interval fusion with preference aggregation (IF&PA) method is proposed to be used, which was proved to be robust and accurate when processing heteroscedastic data. The method forms a profile of rankings of discrete values obtained by partition of the range of actual values (RAV) being a union of input intervals to be adjusted; determines the profile consensus ranking; and the highest ranked consensus value is accepted as a fusion result x. A nonlinear effect of the RAV partition norm on x is studied. IF&PA, redesigned to obtain more accurate result x , was experimentally tested when adjusting the Planck constant values on both random input data and real life values used in the CODATA adjustments 2006 and 2017. It is shown the IF&PA works well with no statistical assumptions and provides adjusted result x with tangibly reduced uncertainty in contrast to traditional Birge ratio methods.
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650		4	\|a Preference aggregation
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650		4	\|a Consensus estimate
650		4	\|a Ranking
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allfields	10.1016/j.measurement.2020.108037 doi (DE-627)ELV004687620 (ELSEVIER)S0263-2241(20)30575-3 DE-627 ger DE-627 rda eng 660 DE-600 50.21 bkl Muravyov, Sergey V. verfasserin aut Adjustment of fundamental physical constant values using the interval fusion with preference aggregation 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier For adjustment of fundamental constants, the interval fusion with preference aggregation (IF&PA) method is proposed to be used, which was proved to be robust and accurate when processing heteroscedastic data. The method forms a profile of rankings of discrete values obtained by partition of the range of actual values (RAV) being a union of input intervals to be adjusted; determines the profile consensus ranking; and the highest ranked consensus value is accepted as a fusion result x. A nonlinear effect of the RAV partition norm on x is studied. IF&PA, redesigned to obtain more accurate result x , was experimentally tested when adjusting the Planck constant values on both random input data and real life values used in the CODATA adjustments 2006 and 2017. It is shown the IF&PA works well with no statistical assumptions and provides adjusted result x with tangibly reduced uncertainty in contrast to traditional Birge ratio methods. Interval fusion Preference aggregation Fundamental constant adjustment Consensus estimate Ranking Khudonogova, Liudmila I. verfasserin aut Ho, Minh Dai verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 163 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:163 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.21 Messtechnik AR 163
spelling	10.1016/j.measurement.2020.108037 doi (DE-627)ELV004687620 (ELSEVIER)S0263-2241(20)30575-3 DE-627 ger DE-627 rda eng 660 DE-600 50.21 bkl Muravyov, Sergey V. verfasserin aut Adjustment of fundamental physical constant values using the interval fusion with preference aggregation 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier For adjustment of fundamental constants, the interval fusion with preference aggregation (IF&PA) method is proposed to be used, which was proved to be robust and accurate when processing heteroscedastic data. The method forms a profile of rankings of discrete values obtained by partition of the range of actual values (RAV) being a union of input intervals to be adjusted; determines the profile consensus ranking; and the highest ranked consensus value is accepted as a fusion result x. A nonlinear effect of the RAV partition norm on x is studied. IF&PA, redesigned to obtain more accurate result x , was experimentally tested when adjusting the Planck constant values on both random input data and real life values used in the CODATA adjustments 2006 and 2017. It is shown the IF&PA works well with no statistical assumptions and provides adjusted result x with tangibly reduced uncertainty in contrast to traditional Birge ratio methods. Interval fusion Preference aggregation Fundamental constant adjustment Consensus estimate Ranking Khudonogova, Liudmila I. verfasserin aut Ho, Minh Dai verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 163 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:163 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.21 Messtechnik AR 163
allfields_unstemmed	10.1016/j.measurement.2020.108037 doi (DE-627)ELV004687620 (ELSEVIER)S0263-2241(20)30575-3 DE-627 ger DE-627 rda eng 660 DE-600 50.21 bkl Muravyov, Sergey V. verfasserin aut Adjustment of fundamental physical constant values using the interval fusion with preference aggregation 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier For adjustment of fundamental constants, the interval fusion with preference aggregation (IF&PA) method is proposed to be used, which was proved to be robust and accurate when processing heteroscedastic data. The method forms a profile of rankings of discrete values obtained by partition of the range of actual values (RAV) being a union of input intervals to be adjusted; determines the profile consensus ranking; and the highest ranked consensus value is accepted as a fusion result x. A nonlinear effect of the RAV partition norm on x is studied. IF&PA, redesigned to obtain more accurate result x , was experimentally tested when adjusting the Planck constant values on both random input data and real life values used in the CODATA adjustments 2006 and 2017. It is shown the IF&PA works well with no statistical assumptions and provides adjusted result x with tangibly reduced uncertainty in contrast to traditional Birge ratio methods. Interval fusion Preference aggregation Fundamental constant adjustment Consensus estimate Ranking Khudonogova, Liudmila I. verfasserin aut Ho, Minh Dai verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 163 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:163 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.21 Messtechnik AR 163
allfieldsGer	10.1016/j.measurement.2020.108037 doi (DE-627)ELV004687620 (ELSEVIER)S0263-2241(20)30575-3 DE-627 ger DE-627 rda eng 660 DE-600 50.21 bkl Muravyov, Sergey V. verfasserin aut Adjustment of fundamental physical constant values using the interval fusion with preference aggregation 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier For adjustment of fundamental constants, the interval fusion with preference aggregation (IF&PA) method is proposed to be used, which was proved to be robust and accurate when processing heteroscedastic data. The method forms a profile of rankings of discrete values obtained by partition of the range of actual values (RAV) being a union of input intervals to be adjusted; determines the profile consensus ranking; and the highest ranked consensus value is accepted as a fusion result x. A nonlinear effect of the RAV partition norm on x is studied. IF&PA, redesigned to obtain more accurate result x , was experimentally tested when adjusting the Planck constant values on both random input data and real life values used in the CODATA adjustments 2006 and 2017. It is shown the IF&PA works well with no statistical assumptions and provides adjusted result x with tangibly reduced uncertainty in contrast to traditional Birge ratio methods. Interval fusion Preference aggregation Fundamental constant adjustment Consensus estimate Ranking Khudonogova, Liudmila I. verfasserin aut Ho, Minh Dai verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 163 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:163 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.21 Messtechnik AR 163
allfieldsSound	10.1016/j.measurement.2020.108037 doi (DE-627)ELV004687620 (ELSEVIER)S0263-2241(20)30575-3 DE-627 ger DE-627 rda eng 660 DE-600 50.21 bkl Muravyov, Sergey V. verfasserin aut Adjustment of fundamental physical constant values using the interval fusion with preference aggregation 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier For adjustment of fundamental constants, the interval fusion with preference aggregation (IF&PA) method is proposed to be used, which was proved to be robust and accurate when processing heteroscedastic data. The method forms a profile of rankings of discrete values obtained by partition of the range of actual values (RAV) being a union of input intervals to be adjusted; determines the profile consensus ranking; and the highest ranked consensus value is accepted as a fusion result x. A nonlinear effect of the RAV partition norm on x is studied. IF&PA, redesigned to obtain more accurate result x , was experimentally tested when adjusting the Planck constant values on both random input data and real life values used in the CODATA adjustments 2006 and 2017. It is shown the IF&PA works well with no statistical assumptions and provides adjusted result x with tangibly reduced uncertainty in contrast to traditional Birge ratio methods. Interval fusion Preference aggregation Fundamental constant adjustment Consensus estimate Ranking Khudonogova, Liudmila I. verfasserin aut Ho, Minh Dai verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 163 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:163 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.21 Messtechnik AR 163
language	English
source	Enthalten in Measurement 163 volume:163
sourceStr	Enthalten in Measurement 163 volume:163
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topic_facet	Interval fusion Preference aggregation Fundamental constant adjustment Consensus estimate Ranking
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authorswithroles_txt_mv	Muravyov, Sergey V. @@aut@@ Khudonogova, Liudmila I. @@aut@@ Ho, Minh Dai @@aut@@
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author	Muravyov, Sergey V.
spellingShingle	Muravyov, Sergey V. ddc 660 bkl 50.21 misc Interval fusion misc Preference aggregation misc Fundamental constant adjustment misc Consensus estimate misc Ranking Adjustment of fundamental physical constant values using the interval fusion with preference aggregation
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topic_title	660 DE-600 50.21 bkl Adjustment of fundamental physical constant values using the interval fusion with preference aggregation Interval fusion Preference aggregation Fundamental constant adjustment Consensus estimate Ranking
topic	ddc 660 bkl 50.21 misc Interval fusion misc Preference aggregation misc Fundamental constant adjustment misc Consensus estimate misc Ranking
topic_unstemmed	ddc 660 bkl 50.21 misc Interval fusion misc Preference aggregation misc Fundamental constant adjustment misc Consensus estimate misc Ranking
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title	Adjustment of fundamental physical constant values using the interval fusion with preference aggregation
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title_full	Adjustment of fundamental physical constant values using the interval fusion with preference aggregation
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title_sort	adjustment of fundamental physical constant values using the interval fusion with preference aggregation
title_auth	Adjustment of fundamental physical constant values using the interval fusion with preference aggregation
abstract	For adjustment of fundamental constants, the interval fusion with preference aggregation (IF&PA) method is proposed to be used, which was proved to be robust and accurate when processing heteroscedastic data. The method forms a profile of rankings of discrete values obtained by partition of the range of actual values (RAV) being a union of input intervals to be adjusted; determines the profile consensus ranking; and the highest ranked consensus value is accepted as a fusion result x. A nonlinear effect of the RAV partition norm on x is studied. IF&PA, redesigned to obtain more accurate result x , was experimentally tested when adjusting the Planck constant values on both random input data and real life values used in the CODATA adjustments 2006 and 2017. It is shown the IF&PA works well with no statistical assumptions and provides adjusted result x with tangibly reduced uncertainty in contrast to traditional Birge ratio methods.
abstractGer	For adjustment of fundamental constants, the interval fusion with preference aggregation (IF&PA) method is proposed to be used, which was proved to be robust and accurate when processing heteroscedastic data. The method forms a profile of rankings of discrete values obtained by partition of the range of actual values (RAV) being a union of input intervals to be adjusted; determines the profile consensus ranking; and the highest ranked consensus value is accepted as a fusion result x. A nonlinear effect of the RAV partition norm on x is studied. IF&PA, redesigned to obtain more accurate result x , was experimentally tested when adjusting the Planck constant values on both random input data and real life values used in the CODATA adjustments 2006 and 2017. It is shown the IF&PA works well with no statistical assumptions and provides adjusted result x with tangibly reduced uncertainty in contrast to traditional Birge ratio methods.
abstract_unstemmed	For adjustment of fundamental constants, the interval fusion with preference aggregation (IF&PA) method is proposed to be used, which was proved to be robust and accurate when processing heteroscedastic data. The method forms a profile of rankings of discrete values obtained by partition of the range of actual values (RAV) being a union of input intervals to be adjusted; determines the profile consensus ranking; and the highest ranked consensus value is accepted as a fusion result x. A nonlinear effect of the RAV partition norm on x is studied. IF&PA, redesigned to obtain more accurate result x , was experimentally tested when adjusting the Planck constant values on both random input data and real life values used in the CODATA adjustments 2006 and 2017. It is shown the IF&PA works well with no statistical assumptions and provides adjusted result x with tangibly reduced uncertainty in contrast to traditional Birge ratio methods.
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title_short	Adjustment of fundamental physical constant values using the interval fusion with preference aggregation
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author2	Khudonogova, Liudmila I. Ho, Minh Dai
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doi_str	10.1016/j.measurement.2020.108037
up_date	2024-07-06T23:49:41.722Z
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Adjustment of fundamental physical constant values using the interval fusion with preference aggregation

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