Prediction of Electricity Trade Partners Based on the Network Theory: The West Asia Community

IF 1.1 Q4 BUSINESS
Leila Mirtajadini, Shamsollah Shirin Bakhsh, M. Mousavi, Kioumars Heydari, S. Yousefvand
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引用次数: 0

Abstract

This study aims to predict electricity cross-border trade partners based on the network theory and to investigate the position and importance of West Asia community in the global electricity trade network. For this purpose, the global network is constructed to examine the role of each node in the network for the time period of 2010–2018. Different communities are identified to proceed with the network analysis. The innovative analysis is link prediction to forecast missing links from the network. The results suggest more interconnectedness among community members, especially Iran, Turkey and Russia, which are the prominent nodes in the community. The link prediction outcomes offer the most probable missing links from the community and lead us to select the common neighbour approach as the most efficient method. JEL Codes: D85, Q27
基于网络理论的电力贸易伙伴预测——以西亚共同体为例
本研究旨在基于网络理论对电力跨境贸易伙伴进行预测,探讨西亚社区在全球电力贸易网络中的地位和重要性。为此,构建了全球网络,以检查2010-2018年期间网络中每个节点的作用。确定了不同的社区以进行网络分析。创新的分析是链路预测,以预测网络中的缺失链路。结果表明,社区成员之间的相互联系更加紧密,特别是伊朗、土耳其和俄罗斯,它们是社区的突出节点。链路预测结果提供了社区中最可能缺失的链路,并引导我们选择共同邻居方法作为最有效的方法。JEL代码:D85, Q27
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来源期刊
CiteScore
2.50
自引率
23.10%
发文量
37
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