Abstract
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 selected stations show that passenger trains are mainly stationary time series otherwise 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.
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Acknowledgement
This article has been created with the support of the student project IGA_PrF_2019_014 of the Palacky University Olomouc.
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Dobesova, Z., Kucera, M. (2019). Time Series of Workload on Railway Routes. In: Silhavy, R. (eds) Artificial Intelligence Methods in Intelligent Algorithms. CSOC 2019. Advances in Intelligent Systems and Computing, vol 985. Springer, Cham. https://doi.org/10.1007/978-3-030-19810-7_37
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DOI: https://doi.org/10.1007/978-3-030-19810-7_37
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