Nowadays, rails are one of the most popular forms of transportation. It is related to the relatively lower costs of the tickets in comparison to airplanes or even costs connected with travelling by car. It needs to be pointed out that this type of transportation has also one important issue that must be addressed. It is connected to the selection of the appropriate train type for all interested passengers. It is extremely hard especially when passengers’ pileups are observed. In this work, we would like to propose an idea to consume time-series data for prediction of the passengers’ flow in one, selected train station that is Łόdź, Poland. Diversified algorithms that can be used directly in these data were presented and our own ideas are given. We would like to also propose our own pipeline built on the basis of all analyzed approaches.


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    Titel :

    Time series for rail passengers flow prediction: a survey


    Beteiligte:


    Erscheinungsdatum :

    27.08.2024


    Format / Umfang :

    734736 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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