A distance-based tool-set to track inconsistent urban structures through complex-networks
Abstract
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.
Cite
@article{arxiv.1803.09136,
title = {A distance-based tool-set to track inconsistent urban structures through complex-networks},
author = {Gabriel Spadon and Bruno B. Machado and Danilo M. Eler and Jose Fernando Rodrigues-Jr},
journal= {arXiv preprint arXiv:1803.09136},
year = {2018}
}
Comments
Paper to be published on the International Conference on Computational Science (ICCS), 2018