Novel Compositional Data's Grey Model for Structurally Forecasting Arctic Crude Oil Import

The reserve of crude oil in the Arctic area is abundant. Ice melting is making it possible to have intermediate access to the Arctic crude oil and its transportation. A novel compositional data's grey model is proposed in this paper to structurally forecast Arctic crude oil import. Firstly, the...

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Bibliographic Details
Main Authors: Qilong, Pan, Jieru, Yin, Xinping, Xiao
Format: Article in Journal/Newspaper
Language:unknown
Published: arXiv 2020
Subjects:
Applications stat.AP
FOS Computer and information sciences
Arctic
Online Access:https://dx.doi.org/10.48550/arxiv.2011.01501
https://arxiv.org/abs/2011.01501
id ftdatacite:10.48550/arxiv.2011.01501
record_format openpolar
spelling ftdatacite:10.48550/arxiv.2011.01501 2023-05-15T14:41:25+02:00 Novel Compositional Data's Grey Model for Structurally Forecasting Arctic Crude Oil Import Qilong, Pan Jieru, Yin Xinping, Xiao 2020 https://dx.doi.org/10.48550/arxiv.2011.01501 https://arxiv.org/abs/2011.01501 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Applications stat.AP FOS Computer and information sciences Article CreativeWork article Preprint 2020 ftdatacite https://doi.org/10.48550/arxiv.2011.01501 2022-03-10T15:01:19Z The reserve of crude oil in the Arctic area is abundant. Ice melting is making it possible to have intermediate access to the Arctic crude oil and its transportation. A novel compositional data's grey model is proposed in this paper to structurally forecast Arctic crude oil import. Firstly, the general accumulative operation sequence of multivariate compositional data is defined according to Aitchison geometry, then obtaining the novel model with the form of the compositional data vectors. Secondly, this paper studies the least square parameter estimation of the model. The novel model is deduced and selected as the time-response expression of the solution. Thirdly, this paper infuses the novel model with traditional grey model to improve its robustness. Differential Evolution algorithm is introduced to determine the optimal value of the general matrix. Lastly, two validation examples are provided for confirming the effectiveness of the novel model by comparing it with other existing models, before being employed to forecast the crude oil import structure in China. The results show that the novel model provides better performance in all crude oil cases in short-term forecasting. Therefore, by using the new model, China's development parameter is 0.5214 and Determination Factor of the novel model is 0.5999, which means that the crude oil import structure of China is being changed. Specifically, the amount of crude oil imported from the Arctic area is obviously increasing in the next 6 years, showing sufficient proof of the edge owned by the Arctic area: abundant crude oil reserves and shortening transportation distance. : 22 pages, 14 figures Article in Journal/Newspaper Arctic DataCite Metadata Store (German National Library of Science and Technology) Arctic
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Applications stat.AP
FOS Computer and information sciences
spellingShingle Applications stat.AP
FOS Computer and information sciences
Qilong, Pan
Jieru, Yin
Xinping, Xiao
Novel Compositional Data's Grey Model for Structurally Forecasting Arctic Crude Oil Import
topic_facet Applications stat.AP
FOS Computer and information sciences
description The reserve of crude oil in the Arctic area is abundant. Ice melting is making it possible to have intermediate access to the Arctic crude oil and its transportation. A novel compositional data's grey model is proposed in this paper to structurally forecast Arctic crude oil import. Firstly, the general accumulative operation sequence of multivariate compositional data is defined according to Aitchison geometry, then obtaining the novel model with the form of the compositional data vectors. Secondly, this paper studies the least square parameter estimation of the model. The novel model is deduced and selected as the time-response expression of the solution. Thirdly, this paper infuses the novel model with traditional grey model to improve its robustness. Differential Evolution algorithm is introduced to determine the optimal value of the general matrix. Lastly, two validation examples are provided for confirming the effectiveness of the novel model by comparing it with other existing models, before being employed to forecast the crude oil import structure in China. The results show that the novel model provides better performance in all crude oil cases in short-term forecasting. Therefore, by using the new model, China's development parameter is 0.5214 and Determination Factor of the novel model is 0.5999, which means that the crude oil import structure of China is being changed. Specifically, the amount of crude oil imported from the Arctic area is obviously increasing in the next 6 years, showing sufficient proof of the edge owned by the Arctic area: abundant crude oil reserves and shortening transportation distance. : 22 pages, 14 figures
format Article in Journal/Newspaper
author Qilong, Pan
Jieru, Yin
Xinping, Xiao
author_facet Qilong, Pan
Jieru, Yin
Xinping, Xiao
author_sort Qilong, Pan
title Novel Compositional Data's Grey Model for Structurally Forecasting Arctic Crude Oil Import
title_short Novel Compositional Data's Grey Model for Structurally Forecasting Arctic Crude Oil Import
title_full Novel Compositional Data's Grey Model for Structurally Forecasting Arctic Crude Oil Import
title_fullStr Novel Compositional Data's Grey Model for Structurally Forecasting Arctic Crude Oil Import
title_full_unstemmed Novel Compositional Data's Grey Model for Structurally Forecasting Arctic Crude Oil Import
title_sort novel compositional data's grey model for structurally forecasting arctic crude oil import
publisher arXiv
publishDate 2020
url https://dx.doi.org/10.48550/arxiv.2011.01501
https://arxiv.org/abs/2011.01501
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_rights arXiv.org perpetual, non-exclusive license
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
op_doi https://doi.org/10.48550/arxiv.2011.01501
_version_ 1766313190405177344

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