THE USE OF NEURAL NETWORKS TO FORECAST THE NUMBER OF ROAD ACCIDENTS IN POLAND

Autor: Piotr GORZELANCZYK
Jazyk: English<br />Polish
Rok vydání: 2023
Předmět:
Zdroj: Scientific Journal of Silesian University of Technology. Series Transport, Vol 118, Pp 45-54 (2023)
Druh dokumentu: article
ISSN: 0209-3324
2450-1549
DOI: 10.20858/sjsutst.2023.118.4
Popis: Every year, a large number of traffic accidents occur on Polish roads. However, the pandemic of recent years has reduced the number of these accidents, although the number is still very high. For this reason, all measures should be taken to reduce this number. This article aims to forecast the number of road accidents in Poland. Thus, using Statistica software, the annual data on the number of road accidents in Poland were analyzed. Based on actual past data, a forecast was made for the future, for the period 2022-2040. Forecasting the number of accidents in Poland was conducted using selected neural network models. The results show that a reduction in the number of traffic accidents is likely. The choice of the number of random samples (learning, testing and validation) affects the results obtained.
Databáze: Directory of Open Access Journals