StationRank: Aggregate dynamics of the Swiss railway.

Increasing availability and quality of actual, as opposed to scheduled, open transport data offers new possibilities for capturing the spatiotemporal dynamics of railway and other networks of social infrastructure. One way to describe such complex phenomena is in terms of stochastic processes. At it...

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Main Authors: Georg Anagnostopoulos, Vahid Moosavi
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0244206
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author Georg Anagnostopoulos
Vahid Moosavi
author_facet Georg Anagnostopoulos
Vahid Moosavi
author_sort Georg Anagnostopoulos
collection DOAJ
description Increasing availability and quality of actual, as opposed to scheduled, open transport data offers new possibilities for capturing the spatiotemporal dynamics of railway and other networks of social infrastructure. One way to describe such complex phenomena is in terms of stochastic processes. At its core, a stochastic model is domain-agnostic and algorithms discussed here have been successfully used in other applications, including Google's PageRank citation ranking. Our key assumption is that train routes constitute meaningful sequences analogous to sentences of literary text. A corpus of routes is thus susceptible to the same analytic tool-set as a corpus of sentences. With our experiment in Switzerland, we introduce a method for building Markov Chains from aggregated daily streams of railway traffic data. The stationary distributions under normal and perturbed conditions are used to define systemic risk measures with non-evident, valuable information about railway infrastructure.
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spelling doaj.art-5bfb41d1b9bf4648959be8a8a36ef8ea2022-12-21T17:34:44ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-011512e024420610.1371/journal.pone.0244206StationRank: Aggregate dynamics of the Swiss railway.Georg AnagnostopoulosVahid MoosaviIncreasing availability and quality of actual, as opposed to scheduled, open transport data offers new possibilities for capturing the spatiotemporal dynamics of railway and other networks of social infrastructure. One way to describe such complex phenomena is in terms of stochastic processes. At its core, a stochastic model is domain-agnostic and algorithms discussed here have been successfully used in other applications, including Google's PageRank citation ranking. Our key assumption is that train routes constitute meaningful sequences analogous to sentences of literary text. A corpus of routes is thus susceptible to the same analytic tool-set as a corpus of sentences. With our experiment in Switzerland, we introduce a method for building Markov Chains from aggregated daily streams of railway traffic data. The stationary distributions under normal and perturbed conditions are used to define systemic risk measures with non-evident, valuable information about railway infrastructure.https://doi.org/10.1371/journal.pone.0244206
spellingShingle Georg Anagnostopoulos
Vahid Moosavi
StationRank: Aggregate dynamics of the Swiss railway.
PLoS ONE
title StationRank: Aggregate dynamics of the Swiss railway.
title_full StationRank: Aggregate dynamics of the Swiss railway.
title_fullStr StationRank: Aggregate dynamics of the Swiss railway.
title_full_unstemmed StationRank: Aggregate dynamics of the Swiss railway.
title_short StationRank: Aggregate dynamics of the Swiss railway.
title_sort stationrank aggregate dynamics of the swiss railway
url https://doi.org/10.1371/journal.pone.0244206
work_keys_str_mv AT georganagnostopoulos stationrankaggregatedynamicsoftheswissrailway
AT vahidmoosavi stationrankaggregatedynamicsoftheswissrailway