Time series of workload on railway routes

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F19%3A73597178" target="_blank" >RIV/61989592:15310/19:73597178 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-030-19810-7_37" target="_blank" >http://dx.doi.org/10.1007/978-3-030-19810-7_37</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-19810-7_37" target="_blank" >10.1007/978-3-030-19810-7_37</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Time series of workload on railway routes

Popis výsledku v původním jazyce

The article presents the processing of time series of the workload on railway routes in the Czech Republic. The data for railway stations and signal blocks on routes were processed. The aim is to describe some typical railway stations form the point of structure and workload changes. Both passenger and freight trains are recorded. The descriptive data contains the monthly aggregation of count and weight for passenger and freight trains. Monthly-length correction of data was processed before the evaluation of the time series. Examples of time series for se-lected stations show that passenger trains are mainly stationary time series other-wise the freight trains are non-stationary time series with a trend. Some stations have a sessional component of series in data about freight trains. In that case, it is possible to predict the time series from old previous data.

Název v anglickém jazyce

Time series of workload on railway routes

Popis výsledku anglicky

The article presents the processing of time series of the workload on railway routes in the Czech Republic. The data for railway stations and signal blocks on routes were processed. The aim is to describe some typical railway stations form the point of structure and workload changes. Both passenger and freight trains are recorded. The descriptive data contains the monthly aggregation of count and weight for passenger and freight trains. Monthly-length correction of data was processed before the evaluation of the time series. Examples of time series for se-lected stations show that passenger trains are mainly stationary time series other-wise the freight trains are non-stationary time series with a trend. Some stations have a sessional component of series in data about freight trains. In that case, it is possible to predict the time series from old previous data.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

50703 - Transport planning and social aspects of transport (transport engineering to be 2.1)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Arteficial Intelligence Methods in Intelligent Algorithms

ISBN

978-3-030-19810-7

Počet stran výsledku

11

Strana od-do

370-380

Počet stran knihy

404

Název nakladatele

Springer International Publishing AG, Switzerland

Místo vydání

Cham

Kód UT WoS kapitoly

000503762800037