A Distance-Based Tool-Set to Track Inconsistent Urban Structures Through Complex-Networks
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Data
2018-01-01
Autores
Spadon, Gabriel
Machado, Bruno B.
Eler, Danilo M. [UNESP]
Rodrigues Jr, Jose F.
Shi, Y.
Fu, H.
Tian, Y.
Krzhizhanovskaya, V. V.
Lees, M. H.
Dongarra, J.
Título da Revista
ISSN da Revista
Título de Volume
Editor
Springer
Resumo
Complex networks can be used for modeling street meshes and urban agglomerates. With such a model, many aspects of a city can be investigated to promote a better quality of life to its citizens. Along these lines, this paper proposes a set of distance-based pattern-discovery algorithmic instruments to improve urban structures modeled as complex networks, detecting nodes that lack access from/to points of interest in a given city. Furthermore, we introduce a greedy algorithm that is able to recommend improvements to the structure of a city by suggesting where points of interest are to be placed. We contribute to a thorough process to deal with complex networks, including mathematical modeling and algorithmic innovation. The set of our contributions introduces a systematic manner to treat a recurrent problem of broad interest in cities.
Descrição
Palavras-chave
Complex network, Network analysis, Urban structure
Como citar
Computational Science - Iccs 2018, Pt I. Cham: Springer International Publishing Ag, v. 10860, p. 288-301, 2018.