Collaboration and competition spatial complex networks in regional science

被引：0

作者：

Salcedo-Sanz S. ^{[1
]}

Cornejo-Bueno S. ^{[2
]}

Casillas-Pérez D. ^{[2
]}

Camacho-Gómez C. ^{[3
]}

Cuadra L. ^{[1
]}

Chidean M.I. ^{[2
]}

Caamaño A.J. ^{[2
]}

机构：

[1] Department of Signal Processing and Communications, Universidad de Alcalá, Alcalá de Henares, Madrid

[2] Department of Signal Processing and Communications, Universidad Rey Juan Carlos, Fuenlabrada

[3] Department of Information Systems, Universidad Politécnica de Madrid, Madrid

来源：

Journal of Ambient Intelligence and Humanized Computing | 2024年 / 15卷 / 03期

关键词：

Complex network generation models; Evolutionary computation; Regional science; Spatial complex networks;

D O I：

10.1007/s12652-023-04590-0

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper discusses different spatial complex networks construction models useful in Regional Science, and different associated issues and problems. First, we define two different models of spatial networks: Collaboration (SCN) and Competition (SCtN) network, both based on distances among nodes. We then discuss several problems related to Regional Science in these types of spatial networks, showing alternative cases and possible computational solutions. Evolutionary algorithms are proposed to solve these problems both in SCN and SCtN. The experimental part of the paper is comprehensive, and it discuses several approaches for spatial network modelling and construction by means of different computational experiments and simulations, including the evolution of SCN and SCtN in Regional Science problems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

引用

页码：1995 / 2008

页数：13

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