Publication Details

Time Series Analysis and Prediction Statistical Models for the Duration of the Ship Handling at an Oil Terminal

RUDNITCKAIA Julia and HRUŠKA Tomáš. Time Series Analysis and Prediction Statistical Models for the Duration of the Ship Handling at an Oil Terminal. In: RELIABILITY and STATISTICS in TRANSPORTATION and COMMUNICATION. Lecture Notes in Networks and Systems. Riga: Springer International Publishing, 2017, pp. 127-136. ISBN 978-9984-818-86-3. ISSN 2367-3370.
Czech title
Analýza časových řadů a Statistické modely predikce pro dobu zpracování lodí na ropném terminalu
Type
conference paper
Language
english
Authors
Rudnitckaia Julia, Mgr. (DIFS FIT BUT)
Hruška Tomáš, prof. Ing., CSc. (RCIT FIT BUT)
Keywords
time series, statistical models, ARIMA, time prediction, ship handling, oil terminal
Abstract
This work relates to the whole series of papers aimed at creating a marine transport and logistics process map. This map is a reflection of a real process model (descriptive model) with the possibility of extension (scaling process), determination bottlenecks (traffic jam), detecting of deviations for operational response, representation of different perspectives (control-flow, resources, performance). Also, the map can be used as a basis for prediction and decision making systems. As the object of the study, the port module was chosen, namely its component part - the oil terminal. The analysed process includes the whole ship handling from the moment of its arrival to the port (activity Notice received) till the departure (operation Pilotage). Today there are a huge number of ways to model the processes and the main aim is searching of optimal and effective methods of modern intelligent analysis (from the field of Machine Learning, Data Mining, statistics, Process Mining) for building a process map. 
The main point of this paper is to conduct research of time series and, then, to build statistical prediction model based on obtained characteristics.
At the beginning of the article, the analysed time series is presented, which shows the distribution of the ship handling duration for the last 3 years. The main components of the time series, an explanation of their values and their effect on the prediction model are given below. In this article, the famous statistical model auto regression integrated moving average (ARIMA) was chosen for the prediction. The paper presents the results of its application to the port data, the advantages and disadvantages are indicated.
Published
2017
Pages
127-136
Journal
Lecture Notes in Networks and Systems, no. 36, ISSN 2367-3370
Proceedings
RELIABILITY and STATISTICS in TRANSPORTATION and COMMUNICATION
Series
Lecture Notes in Networks and Systems
Conference
Reliability and Statistics in Transportation and Communication, Riga, LV
ISBN
978-9984-818-86-3
Publisher
Springer International Publishing
Place
Riga, LV
DOI
BibTeX
@INPROCEEDINGS{FITPUB11538,
   author = "Julia Rudnitckaia and Tom\'{a}\v{s} Hru\v{s}ka",
   title = "Time Series Analysis and Prediction Statistical Models for the Duration of the Ship Handling at an Oil Terminal",
   pages = "127--136",
   booktitle = "RELIABILITY and STATISTICS in TRANSPORTATION and COMMUNICATION",
   series = "Lecture Notes in Networks and Systems",
   journal = "Lecture Notes in Networks and Systems",
   number = 36,
   year = 2017,
   location = "Riga, LV",
   publisher = "Springer International Publishing",
   ISBN = "978-9984-818-86-3",
   ISSN = "2367-3370",
   doi = "10.1007/978-3-319-74454-4\_12",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11538"
}
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