混合预测模型在阿尔及利亚道路交通事故中的应用

IF 0.3 Q4 ECONOMICS
F. Chellai
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引用次数: 0

摘要

道路交通事故是公众日益关注的健康问题。在这项研究中,我们重点分析和预测了阿尔及利亚2015年至2020年期间的月度事故数量、受伤人数和死亡人数。为此,我们拟合了基于等权重和样本内误差的混合预测模型,并将其与季节自回归移动平均(SARIMA)模型进行了比较。保留到2022年用于预测的三个模型都是混合模型,一个基于等权重,两个基于样本内误差(使用RMSE指标)。此外,混合模型在短期(6个月)、中期(12个月)和长期(24个月)的表现优于SARIMA模型。预测结果显示,我们预计在未来12个月内,事故数量、死亡人数和受伤人数将增加。政策制定者必须加强预防和道路安全战略,尤其是在死亡率最高的农村地区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of the Hybrid Forecasting Models to Road Traffic Accidents in Algeria
Road traffic accidents are a growing public health concern. In this study, we focused on analyzing and forecasting the monthly number of accidents, number of injuries, and number of deaths in Algeria over the period (2015–2020). For this purpose, hybrid forecasting models based on equal weights and in-sample errors were fitted, and we compared them with the seasonal autoregressive moving average (SARIMA) models. The three models retained for forecasting until 2022 are all hybrid models, one based on equal weight and two models based on in-sample errors (using the RMSE indicator). Furthermore, the hybrid models outperformed the SARIMA models for short (6 months), medium (12 months), and long horizon (24 months). The forecasting results showed that we expect an increase in the number of accidents, the number of deaths, and the number of injuries over the next 12 months. Policymakers must enhance strategies for prevention and road safety, especially in rural areas, where the highest rate of fatalities is recorded.
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来源期刊
CiteScore
0.60
自引率
0.00%
发文量
23
审稿时长
24 weeks
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