Difference between revisions of "Optimizing public transportation services"

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''This page is about the applications of machine learning (ML) in the context of optimizing public transport. For an overview of public transport more generally, please see the [https://en.wikipedia.org/wiki/Public_transport Wikipedia page] on this topic.''
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So that many commuters use public transportation services, more energy-efficient that private vehicles, this services must propose time-efficient and reliable options. ML can be used in various ways, for example by predicting bus arrival time and their uncertainty.
 
So that many commuters use public transportation services, more energy-efficient that private vehicles, this services must propose time-efficient and reliable options. ML can be used in various ways, for example by predicting bus arrival time and their uncertainty.

Latest revision as of 15:00, 26 August 2021

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This page is about the applications of machine learning (ML) in the context of optimizing public transport. For an overview of public transport more generally, please see the Wikipedia page on this topic.


So that many commuters use public transportation services, more energy-efficient that private vehicles, this services must propose time-efficient and reliable options. ML can be used in various ways, for example by predicting bus arrival time and their uncertainty.

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