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基于关键节点积极效应模型的快递物流网络点集挖掘

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针对快递物流网络中点集挖掘问题,基于关键节点积极效应模型构建DW-KPP-Pos模型,并设计一种启发式算法提升模型运算效率.对中国快递物流网络的实证分析表明:融合启发式算法的DW-KPP-Pos模型可高效挖掘快递物流网络中的"最大传播点集",该集合成员包括上海市、重庆市、广州市、北京市、金华市和香港特别行政区;计量结果对比显示,DW-KPP-Pos模型所挖掘的点集K,相对点度数点集Kdeg、PageRank点集Kpag和中介中心性点集Kbet,传播效率分别高出0.59%、0.88%和 6.19%.
Nodes-set Mining of Express Logistics Network Based on the Key Player Problem-positive Model
Aiming at the problem of nodes-set mining in express logistics network,this paper con-structs DW-KPP-Pos(Directed Weighted-Key Players Problem-Positive)model based on KPP-Pos(Key Player Problem-Positive)and designs a heuristic algorithm to improve the efficiency of the model.The empirical analysis of China's urban express logistics network shows that:The DW-KPP-Pos model with heuristic algorithm can efficiently mine"Maximum spread seeds group"in express logistics network.Including Shanghai,Chongqing,Guangzhou,Beijing,Jinhua and Hong Kong;The comparison of measurement results suggest that the propagation efficiency of nodes-set K mined by DW-KPP-Pos model is 0.59%,0.88%and 6.19%higher than that of de-gree nodes-set Kdeg,PageRank nodes-set Kpag and betweenness centrality nodes-set Kbet respective-ly.In this paper,a new method of nodes-set mining considering maximum spread effect is pro-posed,which can provide technical support for the layout of express logistics infrastructure.

complex networknodes-set mining methodDW-KPP-Pos modelexpress logisticsheuristic algorithm

吴旗韬、李苑庭、吴海玲、杨昀昊、武俊强

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广东省科学院广州地理研究所,广州 510070

华南师范大学地理科学学院,广州 510631

广东工业大学建筑与城市规划学院,广州 510090

国芯科技(广州)有限公司,广州 510700

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复杂网络 点集挖掘方法 DW-KPP-Pos模型 快递物流 启发式算法

2024

复杂系统与复杂性科学
青岛大学

复杂系统与复杂性科学

CSTPCD北大核心
影响因子:0.798
ISSN:1672-3813
年,卷(期):2024.21(4)