Caracterização topológica de redes viárias por meio da análise de vetores de características e técnicas de agrupamento
Resumo
As redes complexas contribuem para a pesquisa computacional por sua capacidade de projetar sistemas modelados por vértices e arestas. Eles fornecem meios para descrever estruturas urbanas por meio das malhas viárias, expressando predicados que se referem ao fluxo e ao transporte em zonas urbanas. Este trabalho tem o objetivo de descrever as interações entre diferentes cidades usando seus vetores de características pela análise de informações viárias e das métricas inerentes aos seus elementos. Propõe-se uma análise baseada no uso de mapas digitais, pois permitem abordagens para modelagem de dados e extração de características que suportam atividades analíticas. Os resultados deste trabalho são baseados na análise de 645 cidades, que formam o estado brasileiro de São Paulo; tais resultados demonstram como características extraídas por métricas de grafos descrevem indicadores urbanos que estão enraizados na topologia da rede, e como podem revelar diferenças entre cidades distintas.
Palavras-chave:
Vetor de características, agrupamento, redes viárias, mapas digitais
Referências
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Crucitti, P., Latora, V., and Porta, S. (2006). Centrality measures in spatial networks of urban streets. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 73(3).
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Grauwin, S., Sobolevsky, S., Moritz, S., Godor, I., and Ratti, C. (2015). Towards a comparative science of cities: Using mobile traffic records in new york, london, and hong kong. In Computational approaches for urban environments, pages 363–387. Springer International
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Masucci, A. P., Stanilov, K., and Batty, M. (2013). Limited Urban Growth: London’s Street Network Dynamics since the 18th Century. PLoS ONE, 8(8).
Pan, G., Qi, G., Zhang, W., Li, S., Wu, Z., and Yang, L. T. (2013). Trace analysis and mining for smart cities: issues, methods, and applications. IEEE Communications Magazine, 51(6):120–126.
Porta, S., Crucitti, P., and Latora, V. (2006a). The network analysis of urban streets: A dual approach. Physica A: Statistical Mechanics and its Applications, 369(2):853–866.
Porta, S., Crucitti, P., and Latora, V. (2006b). The Network Analysis of Urban Streets: A Primal Approach. Environment and Planning B: Planning and Design, 33(5):705–725.
Porta, S., Latora, V., Wang, F., Strano, E., Cardillo, A., Scellato, S., Iacoviello, V., and Messora, R. (2009). Street Centrality and Densities of Retail and Services in Bologna, Italy. Environment and Planning B: Planning and Design, 36(3):450–465.
Scripps, J., Nussbaum, R., Tan, P.-N., and Esfahanian, A.-H. (2010). Link-Based Network Mining. In Structural Analysis of Complex Networks, pages 403–419. Springer Nature.
Spadon, G., Gimenes, G., and Rodrigues-Jr, J. F. (2017). Identifying Urban Inconsistencies via Street Networks. volume 108, pages 18 – 27. Elsevier BV. International Conference on Computational Science, ICCS 2017, 12-14 June 2017, Zurich, Switzerland.
Spiwok, V., Oborsky, P., Pazurikova, J., Keenek, A., and Kralova, B. (2015). Nonlinear vs. linear biasing in trp-cage folding simulations. The Journal of Chemical Physics, 142(11).
Strano, E., Nicosia, V., Latora, V., Porta, S., and Barthelemy, M. (2012). Elementary processes governing the evolution of road networks. Scientific Reports, 2.
Strano, E., Viana, M., Costa, L. F., Cardillo, A., Porta, S., and Latora, V. (2013). Urban Street Networks, a Comparative Analysis of Ten European Cities. Environment and Planning B: Planning and Design, 40(6):1071–1086.
Blumer, H. (1971). Social problems as collective behavior. Social problems, 18(3):298–306.
Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., and Hwang, D. (2006). Complex networks: Structure and dynamics. Physics Reports, 424(4-5):175–308.
Chiang, C. (2003). Statistical Methods of Analysis. World Scientific.
Costa, L. F., Rodrigues, F. A., Travieso, G., and Boas, P. R. V. (2007). Characterization of complex networks: A survey of measurements. Advances in Physics, 56(1):167–242.
Costa, L. F., Travenc¸olo, B. A. N., Viana, M. P., and Strano, E. (2010). On the efficiency of transportation systems in large cities. EPL (Europhysics Letters), 91(1).
Crucitti, P., Latora, V., and Porta, S. (2006). Centrality measures in spatial networks of urban streets. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 73(3).
Domingues, G. S., Silva, F. N., Comin, C. H., and Costa, L. F. (2017). Topological characterization of world cities. arXiv preprint arXiv:1709.08244.
Grauwin, S., Sobolevsky, S., Moritz, S., Godor, I., and Ratti, C. (2015). Towards a comparative science of cities: Using mobile traffic records in new york, london, and hong kong. In Computational approaches for urban environments, pages 363–387. Springer International
Konstantopoulos, T. (2012). Introduction to projective geometry. Number September. Dover Publications.
Kremer, H., Kranen, P., Jansen, T., Seidl, T., Bifet, A., Holmes, G., and Pfahringer, B. (2011). An effective evaluation measure for clustering on evolving data streams. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’11, pages 868–876, New York, NY, USA. ACM.
Li, X. and Parrott, L. (2016). An improved genetic algorithm for spatial optimization of multi-objective and multi-site land use allocation. Computers, Environment and Urban Systems, 59:184–194.
MacQueen, J. et al. (1967). Some methods for classification and analysis of multivariate observations. In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, volume 1, pages 281–297.
Masucci, A. P., Stanilov, K., and Batty, M. (2013). Limited Urban Growth: London’s Street Network Dynamics since the 18th Century. PLoS ONE, 8(8).
Pan, G., Qi, G., Zhang, W., Li, S., Wu, Z., and Yang, L. T. (2013). Trace analysis and mining for smart cities: issues, methods, and applications. IEEE Communications Magazine, 51(6):120–126.
Porta, S., Crucitti, P., and Latora, V. (2006a). The network analysis of urban streets: A dual approach. Physica A: Statistical Mechanics and its Applications, 369(2):853–866.
Porta, S., Crucitti, P., and Latora, V. (2006b). The Network Analysis of Urban Streets: A Primal Approach. Environment and Planning B: Planning and Design, 33(5):705–725.
Porta, S., Latora, V., Wang, F., Strano, E., Cardillo, A., Scellato, S., Iacoviello, V., and Messora, R. (2009). Street Centrality and Densities of Retail and Services in Bologna, Italy. Environment and Planning B: Planning and Design, 36(3):450–465.
Scripps, J., Nussbaum, R., Tan, P.-N., and Esfahanian, A.-H. (2010). Link-Based Network Mining. In Structural Analysis of Complex Networks, pages 403–419. Springer Nature.
Spadon, G., Gimenes, G., and Rodrigues-Jr, J. F. (2017). Identifying Urban Inconsistencies via Street Networks. volume 108, pages 18 – 27. Elsevier BV. International Conference on Computational Science, ICCS 2017, 12-14 June 2017, Zurich, Switzerland.
Spiwok, V., Oborsky, P., Pazurikova, J., Keenek, A., and Kralova, B. (2015). Nonlinear vs. linear biasing in trp-cage folding simulations. The Journal of Chemical Physics, 142(11).
Strano, E., Nicosia, V., Latora, V., Porta, S., and Barthelemy, M. (2012). Elementary processes governing the evolution of road networks. Scientific Reports, 2.
Strano, E., Viana, M., Costa, L. F., Cardillo, A., Porta, S., and Latora, V. (2013). Urban Street Networks, a Comparative Analysis of Ten European Cities. Environment and Planning B: Planning and Design, 40(6):1071–1086.
Publicado
25/08/2018
Como Citar
SPADON, Gabriel; SCABORA, Lucas C.; NESSO-JR, Marcos R.; TRAINA-JR, Caetano; RODRIGUES-JR, Jose F..
Caracterização topológica de redes viárias por meio da análise de vetores de características e técnicas de agrupamento. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 33. , 2018, Rio de Janeiro.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 157-168.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2018.22227.
