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Entropy 2017, 19(4), 159; doi:10.3390/e19040159

A Study of the Transfer Entropy Networks on Industrial Electricity Consumption

1
School of Economics and Commerce, South China University of Technology, Guangzhou 510006, China
2
Industrial and Urban Development Research Center, South China University of Technology, Guangzhou 510006, China
3
School of Computer Science & Engineering, South China University of Technology, Guangzhou 510006, China
*
Author to whom correspondence should be addressed.
Academic Editor: Raúl Alcaraz Martínez
Received: 11 January 2017 / Revised: 29 March 2017 / Accepted: 3 April 2017 / Published: 13 April 2017
(This article belongs to the Special Issue Symbolic Entropy Analysis and Its Applications)
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Abstract

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. View Full-Text
Keywords: transfer entropy; minimum spanning tree; industrial electricity consumption; industrial causality mechanism transfer entropy; minimum spanning tree; industrial electricity consumption; industrial causality mechanism
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Yao, C.-Z.; Kuang, P.-C.; Lin, Q.-W.; Sun, B.-Y. A Study of the Transfer Entropy Networks on Industrial Electricity Consumption. Entropy 2017, 19, 159.

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