Predicting The Number of Traffic Accidents Using Box-Jenkins Models to Contribute to Reducing These Accidents (An Applied Study in Baghdad Governorate)
Keywords:
Reported Incidents، Box-Jenkins Models، Predicating، Time Series، ARIMA models
Abstract
This research aims to analyze the time series of the number of recorded accidents in Baghdad during the period using Box-Jenkins models to find the best and most efficient predictive model for the number of accidents during the period. The results، based on comparison criteria (AIC، SCH، HQC) for the significant models and the comparison between the proposed parameters and models، showed that the suitable model for estimating the number of accidents is the ARIMA(1،1،2) model. The predictive values have shown consistency with their counterparts in the time series with the actual values in the trend، indicating the efficiency of the model.
References
1. Agha, Mahdi Saleh Abdul Qadir Qasim, & Zad, Rohat. (2017). Using time series models to predict stock prices in the Saudi stock market. . QALAAI ZANIST JOURNAL, 2(4), 88-107..
2. Benaissa, A. (2020). Data processing applications: lectures supported by examples solved using EVIEWS program Ibn Khaldun University, Algeria.
3. Shaarawy, Samir Mustafa, (2005), Introduction to Modern Time Series Analysis, Faculty of Science, King Abdulaziz University, Scientific Publishing Center, Saudi Arabia.
4. Vandel, Walter (1992) "Time Series from the Applied Point of View and Box and Jenkins Models", book, Arabization and review by Abdul Mardi Hamed Azzam and Ahmed Hussein Haroun, Dar Al-Mars Publishing Press, Saudi Arabia.
5. Al-Metwally, Ahmed Shaker, (1989), "The Use of Time Series Intervention Analysis and its Applications in Environmental Data - Measuring the Degree of Pollution of Tigris River Water, Master Thesis Submitted to the Council of the Faculty of Administration and Economics, Salahaddin University
6. Mustafa, Anwar El-Zein Babiker.2021" Using Box-Jenken Models to Predict Total Gum Arabic Production in Sudan during the Period 1970-2019. Journal of Humanities and Natural Sciences - Issue Four / Volume Two April 2021.
7. Al-Wardi, Adnan Hashem, (1990), Methods of Statistical Forecasting: Methods and Application, 1st Edition, Dar Al-Hikma in Basra, Iraq.
8. Box George، E. P.، Jenkins Gwilym، M.، Reinsel Gregory، C.، & Ljung Greta، M. (1976). Time series analysis: forecasting and control. San Francisco.
9. Box، G. E.، & Pierce، D. A. (1970). Distribution of residual autocorrelations in autoregressive-integrated moving average time series models. Journal of the American statistical Association، 65(332)، 1509-1526
10. Brockwell، P. J.، & Davis، R. A. (1991). Time series: theory and methods. Springer science & business media.
11. Cryer، J. D.، & Chan، K. S. (2008). Time series models of heteroscedasticity. Time Series Analysis: With Applications in R، 277-318.
12. Dickey، D. A.، & Fuller، W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association، 74(366a)، 427-431.
13. Dritsaki, N.، & Klazoglou, P. (2018). Forecasting unemployment rates in USA using Box-Jenkins methodology. International Journal of Economics and Financial Issues، 8(1), P:11
2. Benaissa, A. (2020). Data processing applications: lectures supported by examples solved using EVIEWS program Ibn Khaldun University, Algeria.
3. Shaarawy, Samir Mustafa, (2005), Introduction to Modern Time Series Analysis, Faculty of Science, King Abdulaziz University, Scientific Publishing Center, Saudi Arabia.
4. Vandel, Walter (1992) "Time Series from the Applied Point of View and Box and Jenkins Models", book, Arabization and review by Abdul Mardi Hamed Azzam and Ahmed Hussein Haroun, Dar Al-Mars Publishing Press, Saudi Arabia.
5. Al-Metwally, Ahmed Shaker, (1989), "The Use of Time Series Intervention Analysis and its Applications in Environmental Data - Measuring the Degree of Pollution of Tigris River Water, Master Thesis Submitted to the Council of the Faculty of Administration and Economics, Salahaddin University
6. Mustafa, Anwar El-Zein Babiker.2021" Using Box-Jenken Models to Predict Total Gum Arabic Production in Sudan during the Period 1970-2019. Journal of Humanities and Natural Sciences - Issue Four / Volume Two April 2021.
7. Al-Wardi, Adnan Hashem, (1990), Methods of Statistical Forecasting: Methods and Application, 1st Edition, Dar Al-Hikma in Basra, Iraq.
8. Box George، E. P.، Jenkins Gwilym، M.، Reinsel Gregory، C.، & Ljung Greta، M. (1976). Time series analysis: forecasting and control. San Francisco.
9. Box، G. E.، & Pierce، D. A. (1970). Distribution of residual autocorrelations in autoregressive-integrated moving average time series models. Journal of the American statistical Association، 65(332)، 1509-1526
10. Brockwell، P. J.، & Davis، R. A. (1991). Time series: theory and methods. Springer science & business media.
11. Cryer، J. D.، & Chan، K. S. (2008). Time series models of heteroscedasticity. Time Series Analysis: With Applications in R، 277-318.
12. Dickey، D. A.، & Fuller، W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association، 74(366a)، 427-431.
13. Dritsaki, N.، & Klazoglou, P. (2018). Forecasting unemployment rates in USA using Box-Jenkins methodology. International Journal of Economics and Financial Issues، 8(1), P:11
Published
2025-04-03
How to Cite
Salman, A. A. (2025). Predicting The Number of Traffic Accidents Using Box-Jenkins Models to Contribute to Reducing These Accidents (An Applied Study in Baghdad Governorate). CENTRAL ASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES, 6(3), 279-289. Retrieved from https://cajmtcs.centralasianstudies.org/index.php/CAJMTCS/article/view/749
Section
Articles
