Modeling the Public Transport Networks: A Study of Their Efficiency

The public transportation network (PTN) provides mobility and access to community resources, employment, medical care, infrastructures, and other resources in the city. This research studies the process of the formation of links among nodes in different real-world PTNs. We have found that this proce...

Full description

Saved in:
Bibliographic Details
Main Author: Mary Luz Mouronte-López
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2021/3280777
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850158903065575424
author Mary Luz Mouronte-López
author_facet Mary Luz Mouronte-López
author_sort Mary Luz Mouronte-López
collection DOAJ
description The public transportation network (PTN) provides mobility and access to community resources, employment, medical care, infrastructures, and other resources in the city. This research studies the process of the formation of links among nodes in different real-world PTNs. We have found that this process may be appropriately explained by a generalized linear model (GLM) using local, global, and quasilocal similarity indexes as explanatory variables. In modeling, the response variable was described by a binomial probability density function, and the logit function was used as a link function. In the crossvalidation process, utilising a downsampling approach, both average accuracy and area under the receiver operating characteristic curve (AUC) metrics presented higher values than 0.99. The kappa parameter had magnitudes larger than 0.93 for most of the PTNs. In the final validation stage, recall and specificity metrics took the value 1. Accuracy and precision parameters were larger than 0.99 and 0.87, respectively, for the majority of PTNs. Only one of the PTNs required utilising a smoothed bootstrap approach in order to achieve better results. The similarity measures with the greatest influence on the model were determined. We also assessed the impact of link removal on the global efficiency of PTNs, considering several similarity indexes. Additionally, we find that most of the networks show low local and global efficiencies (≤0.20), as well as travel times with a relevant variability, exhibiting standard deviations larger than 790 seconds. Significant similarities exist between the cumulative probability distributions of the local efficiency in all PTNs. With respect to the centrality measures, the eigenvector centrality presented a strong correlation with the hub/authority centralities (>0.80), while the pagerank showed a moderate, high, or very high correlation with the degree in all PTNs, >0.50.
format Article
id doaj-art-6675ee547e8a416abe7086a27f3d59c4
institution OA Journals
issn 1076-2787
1099-0526
language English
publishDate 2021-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-6675ee547e8a416abe7086a27f3d59c42025-08-20T02:23:44ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/32807773280777Modeling the Public Transport Networks: A Study of Their EfficiencyMary Luz Mouronte-López0Higher Polytechnic School, Universidad Francisco de Vitoria, Madrid, SpainThe public transportation network (PTN) provides mobility and access to community resources, employment, medical care, infrastructures, and other resources in the city. This research studies the process of the formation of links among nodes in different real-world PTNs. We have found that this process may be appropriately explained by a generalized linear model (GLM) using local, global, and quasilocal similarity indexes as explanatory variables. In modeling, the response variable was described by a binomial probability density function, and the logit function was used as a link function. In the crossvalidation process, utilising a downsampling approach, both average accuracy and area under the receiver operating characteristic curve (AUC) metrics presented higher values than 0.99. The kappa parameter had magnitudes larger than 0.93 for most of the PTNs. In the final validation stage, recall and specificity metrics took the value 1. Accuracy and precision parameters were larger than 0.99 and 0.87, respectively, for the majority of PTNs. Only one of the PTNs required utilising a smoothed bootstrap approach in order to achieve better results. The similarity measures with the greatest influence on the model were determined. We also assessed the impact of link removal on the global efficiency of PTNs, considering several similarity indexes. Additionally, we find that most of the networks show low local and global efficiencies (≤0.20), as well as travel times with a relevant variability, exhibiting standard deviations larger than 790 seconds. Significant similarities exist between the cumulative probability distributions of the local efficiency in all PTNs. With respect to the centrality measures, the eigenvector centrality presented a strong correlation with the hub/authority centralities (>0.80), while the pagerank showed a moderate, high, or very high correlation with the degree in all PTNs, >0.50.http://dx.doi.org/10.1155/2021/3280777
spellingShingle Mary Luz Mouronte-López
Modeling the Public Transport Networks: A Study of Their Efficiency
Complexity
title Modeling the Public Transport Networks: A Study of Their Efficiency
title_full Modeling the Public Transport Networks: A Study of Their Efficiency
title_fullStr Modeling the Public Transport Networks: A Study of Their Efficiency
title_full_unstemmed Modeling the Public Transport Networks: A Study of Their Efficiency
title_short Modeling the Public Transport Networks: A Study of Their Efficiency
title_sort modeling the public transport networks a study of their efficiency
url http://dx.doi.org/10.1155/2021/3280777
work_keys_str_mv AT maryluzmourontelopez modelingthepublictransportnetworksastudyoftheirefficiency