PREDICTIVE TOOLS AS PART OF DECISSION AIDING PROCESSES AT THE AIRPORT – THE CASE OF FACEBOOK PROPHET LIBRARY

Sylwester KORGA

s.korga@pollub.pl
Lublin University of Technology (Poland)

Kamil ŻYŁA


Lublin University of Technology (Poland)
https://orcid.org/0000-0002-6291-003X

Jerzy JÓZWIK


Lublin University of Technology (Poland)

Jarosław PYTKA


Lublin University of Technology (Poland)

Kamil CYBUL


Lublin University of Technology, Central Office of Measures (Poland)

Abstract

Prophet is a quite fresh and promising open-source library for machine learning, developed by Facebook, that gains some significant interest. It could be used for predicting time series taking into account holidays and seasonality effects. Its possible applications and deficit of scientific works concerning its usage within decision processes convinced the authors to state the research question, if the Prophet library could provide reliable prediction to support decision-making processes at the airport. The case of Radawiec airport (located near Lublin, Poland) was chosen. Official measurement data (from the last 4 years) published by the Polish Government  Institute was used to train the neural network and predict daily averages of wind speed, temperature, pressure, relative humidity and rainfall totals during the day and night. It was revealed that most of the predicted data points were within the acceptance threshold, and computations were fast and highly automated. However, the authors believe that the Prophet library is not particularly useful for airport decision-making processes because the way it handles additional regressors and susceptibility to unexpected phenomena negatively affects the reliability of prediction results.


Keywords:

weather prediction, Facebook Prophet, aviation, machine learning, Data Analysis

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Published
2023-12-31

Cited by

KORGA, S., ŻYŁA, K., JÓZWIK, J., PYTKA, J., & CYBUL, K. (2023). PREDICTIVE TOOLS AS PART OF DECISSION AIDING PROCESSES AT THE AIRPORT – THE CASE OF FACEBOOK PROPHET LIBRARY. Applied Computer Science, 19(4), 51–67. https://doi.org/10.35784/acs-2023-35

Authors

Sylwester KORGA 
s.korga@pollub.pl
Lublin University of Technology Poland

Authors

Kamil ŻYŁA 

Lublin University of Technology Poland
https://orcid.org/0000-0002-6291-003X

Authors

Jerzy JÓZWIK 

Lublin University of Technology Poland

Authors

Jarosław PYTKA 

Lublin University of Technology Poland

Authors

Kamil CYBUL 

Lublin University of Technology, Central Office of Measures Poland

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