Predicting Road Accident Counts in Poland and the Czech Republic Using Neural Network Models

Rocznik Ochrona Środowiska 2024, vol. 26, pp. 603-615

Piotr Gorzelańczyk¹ , Lenka Ližbetinová² This email address is being protected from spambots. You need JavaScript enabled to view it., Jan Pečman² 

	1. Stanislaw Staszic State University of Applied Sciences in Pila, Poland  2. Institute of Technology and Business in České Budějovice, Czech Republic
	This email address is being protected from spambots. You need JavaScript enabled to view it.
	https://doi.org/10.54740/ros.2024.053

Every year, there is a decline in the number of car accidents reported in Poland, the Czech Republic, and globally. While recent trends due to the pandemic have influenced these figures, the overall rate remains significant. Therefore, it is crucial to take measures aimed at reducing this number. The primary focus of this article is to analyze the traffic accident statistics for Poland and the Czech Republic. Annual data regarding traffic incidents in both countries has been scrutinized to achieve this. Projections for 2024 to 2030 have been developed based on police reports. Various neural network models were utilized to forecast the number of accidents. The findings indicate that the number of traffic incidents is likely to stabilize. This stabilization can be viewed in the context of the increasing number of vehicles on the roads and the expansion of new highways. Additionally, selecting sample sizes for training, testing, and validation is crucial in influencing the results. Forecasting the number of traffic accidents is important for environmental protection, as accidents can lead to air and water pollution and increase noise, negatively affecting human health and ecosystems.

road accident, pandemic, forecasting, neural networks, Poland, Czech Republic

AMA Style
Gorzelańczyk P, Ližbetinová L, Pečman J. Predicting Road Accident Counts in Poland and the Czech Republic Using Neural Network Models. Rocznik Ochrona Środowiska. 2024; 26. https://doi.org/10.54740/ros.2024.053

ACM Style
Gorzelańczyk, P., Ližbetinová, L., Pečman, J. 2024. Predicting Road Accident Counts in Poland and the Czech Republic Using Neural Network Models. Rocznik Ochrona Środowiska. 26. DOI:https://doi.org/10.54740/ros.2024.053

ACS Style
Gorzelańczyk, P.; Ližbetinová, L.; Pečman, J. Predicting Road Accident Counts in Poland and the Czech Republic Using Neural Network Models Rocznik Ochrona Środowiska 2024, 26, 603-615. https://doi.org/10.54740/ros.2024.053

APA Style
Gorzelańczyk, P., Ližbetinová, L., Pečman, J. (2024). Predicting Road Accident Counts in Poland and the Czech Republic Using Neural Network Models. Rocznik Ochrona Środowiska, 26, 603-615. https://doi.org/10.54740/ros.2024.053

ABNT Style
GORZELAŃCZYK, P.; LIŽBETINOVÁ, L.; PEČMAN, J. Predicting Road Accident Counts in Poland and the Czech Republic Using Neural Network Models. Rocznik Ochrona Środowiska, v. 26, p. 603-615, 2024. https://doi.org/10.54740/ros.2024.053

Chicago Style
Gorzelańczyk, Piotr, Ližbetinová, Lenka, Pečman, Jan. 2024. "Predicting Road Accident Counts in Poland and the Czech Republic Using Neural Network Models". Rocznik Ochrona Środowiska 26, 603-615. https://doi.org/10.54740/ros.2024.053

Harvard Style
Gorzelańczyk, P., Ližbetinová, L., Pečman, J. (2024) "Predicting Road Accident Counts in Poland and the Czech Republic Using Neural Network Models", Rocznik Ochrona Środowiska, 26, pp. 603-615. doi:https://doi.org/10.54740/ros.2024.053

IEEE Style
P. Gorzelańczyk, L. Ližbetinová, J. Pečman, "Predicting Road Accident Counts in Poland and the Czech Republic Using Neural Network Models", RoczOchrSrod, vol 26, pp. 603-615. https://doi.org/10.54740/ros.2024.053