Autor(es): 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. ; Sloot, PMA
Data: 2020
Identificador Persistente: http://hdl.handle.net/11449/196993
Origem: Oasisbr
Assunto(s): Complex network; Network analysis; Urban structure
Made available in DSpace on 2020-12-10T20:02:53Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-01-01
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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.
Univ Sao Paulo, Sao Carlos, SP, Brazil
Univ Fed Mato Grosso do Sul, Ponta Pora, MS, Brazil
Sao Paulo State Univ, Presidente Prudente, SP, Brazil
Sao Paulo State Univ, Presidente Prudente, SP, Brazil
CNPq: 167967/2017-7
FAPESP: 2016/17078-0
FAPESP: 2017/08376-0
