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

IF 0.4 Q4 TRANSPORTATION SCIENCE & TECHNOLOGY Scientific Journal of Silesian University of Technology-Series Transport Pub Date : 2023-03-01 DOI:10.20858/sjsutst.2023.118.4
Piotr Gorzelańczyk
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Abstract

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.
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使用神经网络来预测波兰道路交通事故的数量
每年,波兰的道路上都会发生大量的交通事故。然而,近年来的流行病减少了这些事故的数量,尽管数量仍然很高。出于这个原因,应该采取一切措施来减少这个数字。这篇文章旨在预测波兰道路交通事故的数量。因此,使用Statistica软件,分析了波兰道路交通事故数量的年度数据。根据过去的实际数据,对2022-2040年的未来进行了预测。预测波兰的事故数量是使用选定的神经网络模型进行的。结果表明,交通事故的数量有可能减少。随机样本数量的选择(学习、测试和验证)会影响得到的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.20
自引率
0.00%
发文量
52
审稿时长
20 weeks
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