有向加权城市网络的转变中心性与控制力测度--以中国春运人口流动网络为例

发布时间：2018-06-15 03:32

本文选题：有向加权网络 + 城市网络　；参考：以中国春运人口流动网络为例

【摘要】：目前中国地学领域对网络的研究仍处于起步阶段,大量网络研究方法尚未得到应用的同时,许多地理现象尚未寻找到合适的抽象网络模型,不断拓展和应用有效的网络分析方法成为当务之急。在这一背景下,基于百度迁徙平台获取的春运人口流动大数据,构建中国春运人口流动的有向加权城市网络,在已有研究基础上提出有向转变中心性与控制力测度方法,对该城市网络的节点重要性和功能进行评估和分类,分析其呈现的二维空间特征与地理空间分布特征,并与已有方法进行对比。结果表明:利用有向转变中心性和控制力方法,可有效提取有向加权网络的层级结构、功能分异和非均衡性等特征,不但可区分典型城市、枢纽城市、门户城市与边缘城市等不同的城市类型,还可以识别城市的集聚与扩散特征,从而获得比无权无向网络更为丰富和具有实践意义的信息参考,是一种有效的地理网络分析方法。
[Abstract]:At present, the research on network in the field of geoscience in China is still in its infancy, a large number of network research methods have not yet been applied, and many geographical phenomena have not yet found a suitable abstract network model. It is urgent to develop and apply effective network analysis methods. Under this background, based on the big data obtained by Baidu migration platform, this paper constructs the directional weighted urban network of Chinese spring transportation population mobility, and puts forward the measurement method of oriented transformation centrality and control force on the basis of existing research. This paper evaluates and classifies the importance and function of the nodes of the urban network, analyzes its two-dimensional spatial features and geographical spatial distribution features, and compares them with the existing methods. The results show that the hierarchical structure, functional differentiation and disequilibrium of the directed weighted network can be extracted effectively by using the method of directed transformation centrality and control force, and not only can the typical cities be distinguished from the hub cities, but also the key cities can be distinguished. Different urban types, such as portal city and marginal city, can also identify the characteristics of urban agglomeration and diffusion, thus obtaining more abundant and practical information reference than unauthorized undirected network, which is an effective method of geographical network analysis.
【作者单位】：吉林大学地球科学学院;东北师范大学地理科学学院;
【基金】：国家自然科学基金项目(41401172,41630749)
【分类号】：C912.81

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