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基于空间网络结构分析的经济社会发展试验区评价指标体系。

Evaluation Index System of Economic and Social Development Pilot Area Based on Spatial Network Structure Analysis.

机构信息

School of Economics, Xihua University, Chengdu 610039, China.

出版信息

Comput Intell Neurosci. 2022 May 9;2022:3019440. doi: 10.1155/2022/3019440. eCollection 2022.

DOI:10.1155/2022/3019440
PMID:35586086
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9110125/
Abstract

In order to improve the evaluation effect of the economic and social development pioneer area, this paper constructs the evaluation index system of the economic and social development pioneer area based on the spatial network structure analysis method and obtains an intelligent analysis system. Moreover, from the perspective of economic development information flow, this paper uses information flow direction analysis method and advantage flow analysis method to discuss the structural characteristics of urban economic development network in the economic belt, providing new methods and perspectives for the study of urban economic development flow. In addition, this paper attempts to propose a universal method for quantitative research on the "flow space" structure of urban economic development as the forward-looking content of urban economic development. According to the simulation test results, it can be seen that the evaluation index system of the economic and social development pilot area based on the analysis of the spatial network structure proposed in this paper has a good effect.

摘要

为了提高经济社会发展先行区的评价效果，本文基于空间网络结构分析方法构建了经济社会发展先行区的评价指标体系，并得到了一个智能分析系统。此外，本文从经济发展信息流的角度，采用信息流方向分析方法和优势流分析方法，探讨了经济带中城市经济发展网络的结构特征，为城市经济发展流的研究提供了新的方法和视角。此外，本文还试图提出一种通用的方法，用于定量研究城市经济发展的“流空间”结构，作为城市经济发展的前瞻性内容。根据模拟测试结果，可以看出，本文提出的基于空间网络结构分析的经济社会发展先行区评价指标体系具有较好的效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/700432e9902d/CIN2022-3019440.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/b15b90e71b37/CIN2022-3019440.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/346581fdb548/CIN2022-3019440.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/f42a4aa2896d/CIN2022-3019440.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/9fa17df12b16/CIN2022-3019440.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/22e936eb5be2/CIN2022-3019440.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/729c5d14b746/CIN2022-3019440.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/3215bc637835/CIN2022-3019440.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/455259361c99/CIN2022-3019440.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/700432e9902d/CIN2022-3019440.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/b15b90e71b37/CIN2022-3019440.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/346581fdb548/CIN2022-3019440.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/f42a4aa2896d/CIN2022-3019440.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/9fa17df12b16/CIN2022-3019440.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/22e936eb5be2/CIN2022-3019440.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/729c5d14b746/CIN2022-3019440.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/3215bc637835/CIN2022-3019440.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/455259361c99/CIN2022-3019440.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9110125/700432e9902d/CIN2022-3019440.009.jpg

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