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A Study of the Transfer Entropy Networks on Industrial Electricity Consumption

机译:工业用电量的传递熵网络研究

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摘要

We study information transfer routes among cross-industry and cross-region electricity consumption data based on transfer entropy and the MST (Minimum Spanning Tree) model. First, we characterize the information transfer routes with transfer entropy matrixes, and find that the total entropy transfer of the relatively developed Guangdong Province is lower than others, with significant industrial cluster within the province. Furthermore, using a reshuffling method, we find that driven industries contain much more information flows than driving industries, and are more influential on the degree of order of regional industries. Finally, based on the Chu-Liu-Edmonds MST algorithm, we extract the minimum spanning trees of provincial industries. Individual MSTs show that the MSTs follow a chain-like formation in developed provinces and star-like structures in developing provinces. Additionally, all MSTs with the root of minimal information outflow industrial sector are of chain-form.
机译:我们基于转移熵和MST(最小生成树)模型研究跨行业和跨地区用电量数据之间的信息传递路径。首先,我们用传递熵矩阵来刻画信息传递的路径,发现相对发达的广东省的总熵传递要比其他省低,在该省内具有明显的产业集群。此外,通过改组方法,我们发现驱动产业比驱动产业包含更多的信息流,并且对区域产业的有序度影响更大。最后,基于Chu-Liu-Edmonds MST算法,我们提取了省级产业的最小生成树。各个MST都表明,MST在发达省份呈链状形成,而在发展中省份呈星状结构。此外,所有以信息流出最少的工业部门为根的所有MST都是链形式的。

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