The novel fractional discrete multivariate grey system model and its applications
Fractional order accumulation is a novel and popular tool which is efficient to improve accuracy of the grey models. However, most existing grey models with fractional order accumulation are all developed on the conventional methodology of grey models, which may be inaccurate in the applications. In...
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| Veröffentlicht in: | Applied Mathematical Modelling Jg. 70; S. 402 |
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| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
Elsevier BV
01.06.2019
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| ISSN: | 1088-8691, 0307-904X |
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| Abstract | Fractional order accumulation is a novel and popular tool which is efficient to improve accuracy of the grey models. However, most existing grey models with fractional order accumulation are all developed on the conventional methodology of grey models, which may be inaccurate in the applications. In this paper an existing fractional multivariate grey model with convolution integral is proved to be a biased model, and then a novel fractional discrete multivariate grey model based on discrete modelling technique is proposed, which is proved to be an unbiased model with mathematical analysis and stochastic testing. An algorithm based on the Grey Wolf Optimizer is introduced to optimize the fractional order of the proposed model. Four real world case studies with updated data sets are executed to assess the effectiveness of the proposed model in comparison with nine existing multivariate grey models. The results show that the Grey Wolf Optimizer-based algorithm is very efficient to optimize the fractional order of the proposed model, and the proposed model outperforms other nine models in the all the real world case studies. |
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| AbstractList | Fractional order accumulation is a novel and popular tool which is efficient to improve accuracy of the grey models. However, most existing grey models with fractional order accumulation are all developed on the conventional methodology of grey models, which may be inaccurate in the applications. In this paper an existing fractional multivariate grey model with convolution integral is proved to be a biased model, and then a novel fractional discrete multivariate grey model based on discrete modelling technique is proposed, which is proved to be an unbiased model with mathematical analysis and stochastic testing. An algorithm based on the Grey Wolf Optimizer is introduced to optimize the fractional order of the proposed model. Four real world case studies with updated data sets are executed to assess the effectiveness of the proposed model in comparison with nine existing multivariate grey models. The results show that the Grey Wolf Optimizer-based algorithm is very efficient to optimize the fractional order of the proposed model, and the proposed model outperforms other nine models in the all the real world case studies. |
| Author | Zeng, Bo Xie, Mei Wu, Wenqing Ma, Xin Wu, Xinxing Wang, Yong |
| Author_xml | – sequence: 1 givenname: Xin surname: Ma fullname: Ma, Xin – sequence: 2 givenname: Mei surname: Xie fullname: Xie, Mei – sequence: 3 givenname: Wenqing surname: Wu fullname: Wu, Wenqing – sequence: 4 givenname: Bo surname: Zeng fullname: Zeng, Bo – sequence: 5 givenname: Yong surname: Wang fullname: Wang, Yong – sequence: 6 givenname: Xinxing surname: Wu fullname: Wu, Xinxing |
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