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基于信息熵的区域可持续发展分析——以四川省为例

Regional Sustainable Development Analysis Based on Information Entropy-Sichuan Province as an Example.

作者信息

Liang Xuedong, Si Dongyang, Zhang Xinli

机构信息

School of Economics, Sichuan University, Chengdu 610065, China.

The Economy and Enterprise Development Institute, Sichuan University, Chengdu 610065, China.

出版信息

Int J Environ Res Public Health. 2017 Oct 13;14(10):1219. doi: 10.3390/ijerph14101219.

Abstract

According to the implementation of a scientific development perspective, sustainable development needs to consider regional development, economic and social development, and the harmonious development of society and nature, but regional sustainable development is often difficult to quantify. Through an analysis of the structure and functions of a regional system, this paper establishes an evaluation index system, which includes an economic subsystem, an ecological environmental subsystem and a social subsystem, to study regional sustainable development capacity. A sustainable development capacity measure model for Sichuan Province was established by applying the information entropy calculation principle and the Brusselator principle. Each subsystem and entropy change in a calendar year in Sichuan Province were analyzed to evaluate Sichuan Province's sustainable development capacity. It was found that the established model could effectively show actual changes in sustainable development levels through the entropy change reaction system, at the same time this model could clearly demonstrate how those forty-six indicators from the three subsystems impact on the regional sustainable development, which could make up for the lack of sustainable development research.

摘要

按照科学发展观的要求,可持续发展需兼顾区域发展、经济社会发展以及社会与自然的和谐发展,但区域可持续发展往往难以量化。通过分析区域系统的结构与功能,本文构建了一个评价指标体系,该体系涵盖经济子系统、生态环境子系统和社会子系统,以研究区域可持续发展能力。运用信息熵计算原理和布鲁塞尔振子原理,建立了四川省可持续发展能力测度模型。通过分析四川省各子系统及历年的熵变情况,对四川省的可持续发展能力进行评价。研究发现,所建立的模型能够通过熵变反应系统有效呈现可持续发展水平的实际变化,同时该模型能够清晰展示来自三个子系统的四十六个指标如何对区域可持续发展产生影响,弥补了可持续发展研究的不足。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/afec/5664720/af26941d3b26/ijerph-14-01219-g001.jpg

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