Application of Fractional Grey Forecasting Model in Economic Growth of the Group of Seven
This paper uses the idea of fractional order accumulation instead of the form of grey index, and applies the fractional order accumulation prediction model to the economic growth prediction of the member states of the Group of Seven from 1973 to 2016. By comparing different evaluation indexes such a...
Ausführliche Beschreibung
Autor*in: |
Yumei Liao [verfasserIn] Xu Wang [verfasserIn] Jinrong Wang [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2022 |
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Schlagwörter: |
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Übergeordnetes Werk: |
In: Axioms - MDPI AG, 2012, 11(2022), 4, p 155 |
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Übergeordnetes Werk: |
volume:11 ; year:2022 ; number:4, p 155 |
Links: |
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DOI / URN: |
10.3390/axioms11040155 |
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Katalog-ID: |
DOAJ044432356 |
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10.3390/axioms11040155 doi (DE-627)DOAJ044432356 (DE-599)DOAJ447c4ed4778e4e7a9ef8a30c55a7ea42 DE-627 ger DE-627 rakwb eng QA1-939 Yumei Liao verfasserin aut Application of Fractional Grey Forecasting Model in Economic Growth of the Group of Seven 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper uses the idea of fractional order accumulation instead of the form of grey index, and applies the fractional order accumulation prediction model to the economic growth prediction of the member states of the Group of Seven from 1973 to 2016. By comparing different evaluation indexes such as <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula<, MAD and BIC, it is found that the prediction performance of fractional order cumulative grey prediction model (GM(<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<mi<α</mi<</semantics<</math<</inline-formula<,1)) is significantly improved in the medium and long term compared with the traditional grey prediction model (GM(1,1)). GM(α,1) GM(1,1) economic growth Group of Seven Mathematics Xu Wang verfasserin aut Jinrong Wang verfasserin aut In Axioms MDPI AG, 2012 11(2022), 4, p 155 (DE-627)718622030 (DE-600)2661511-3 20751680 nnns volume:11 year:2022 number:4, p 155 https://doi.org/10.3390/axioms11040155 kostenfrei https://doaj.org/article/447c4ed4778e4e7a9ef8a30c55a7ea42 kostenfrei https://www.mdpi.com/2075-1680/11/4/155 kostenfrei https://doaj.org/toc/2075-1680 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 4, p 155 |
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10.3390/axioms11040155 doi (DE-627)DOAJ044432356 (DE-599)DOAJ447c4ed4778e4e7a9ef8a30c55a7ea42 DE-627 ger DE-627 rakwb eng QA1-939 Yumei Liao verfasserin aut Application of Fractional Grey Forecasting Model in Economic Growth of the Group of Seven 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper uses the idea of fractional order accumulation instead of the form of grey index, and applies the fractional order accumulation prediction model to the economic growth prediction of the member states of the Group of Seven from 1973 to 2016. By comparing different evaluation indexes such as <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula<, MAD and BIC, it is found that the prediction performance of fractional order cumulative grey prediction model (GM(<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<mi<α</mi<</semantics<</math<</inline-formula<,1)) is significantly improved in the medium and long term compared with the traditional grey prediction model (GM(1,1)). GM(α,1) GM(1,1) economic growth Group of Seven Mathematics Xu Wang verfasserin aut Jinrong Wang verfasserin aut In Axioms MDPI AG, 2012 11(2022), 4, p 155 (DE-627)718622030 (DE-600)2661511-3 20751680 nnns volume:11 year:2022 number:4, p 155 https://doi.org/10.3390/axioms11040155 kostenfrei https://doaj.org/article/447c4ed4778e4e7a9ef8a30c55a7ea42 kostenfrei https://www.mdpi.com/2075-1680/11/4/155 kostenfrei https://doaj.org/toc/2075-1680 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 4, p 155 |
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Application of Fractional Grey Forecasting Model in Economic Growth of the Group of Seven |
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This paper uses the idea of fractional order accumulation instead of the form of grey index, and applies the fractional order accumulation prediction model to the economic growth prediction of the member states of the Group of Seven from 1973 to 2016. By comparing different evaluation indexes such as <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula<, MAD and BIC, it is found that the prediction performance of fractional order cumulative grey prediction model (GM(<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<mi<α</mi<</semantics<</math<</inline-formula<,1)) is significantly improved in the medium and long term compared with the traditional grey prediction model (GM(1,1)). |
abstractGer |
This paper uses the idea of fractional order accumulation instead of the form of grey index, and applies the fractional order accumulation prediction model to the economic growth prediction of the member states of the Group of Seven from 1973 to 2016. By comparing different evaluation indexes such as <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula<, MAD and BIC, it is found that the prediction performance of fractional order cumulative grey prediction model (GM(<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<mi<α</mi<</semantics<</math<</inline-formula<,1)) is significantly improved in the medium and long term compared with the traditional grey prediction model (GM(1,1)). |
abstract_unstemmed |
This paper uses the idea of fractional order accumulation instead of the form of grey index, and applies the fractional order accumulation prediction model to the economic growth prediction of the member states of the Group of Seven from 1973 to 2016. By comparing different evaluation indexes such as <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula<, MAD and BIC, it is found that the prediction performance of fractional order cumulative grey prediction model (GM(<inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<mi<α</mi<</semantics<</math<</inline-formula<,1)) is significantly improved in the medium and long term compared with the traditional grey prediction model (GM(1,1)). |
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Application of Fractional Grey Forecasting Model in Economic Growth of the Group of Seven |
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