پیوندهای مفید
آمار
| تعداد نشریات | 8 |
| تعداد شماره‌ها | 422 |
| تعداد مقالات | 5,533 |
| تعداد مشاهده مقاله | 6,399,053 |
| تعداد دریافت فایل اصل مقاله | 5,501,743 |
Analysis of the gasoline consumption on an international scale: A data mining approach | ||
| AUT Journal of Modeling and Simulation | ||
| دوره 55، شماره 2، اسفند 2023، صفحه 275-282 اصل مقاله (607 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/miscj.2024.22687.5340 | ||
| نویسندگان | ||
| Ali Tavakoli Kashani* 1؛ Zahra Sartibi1؛ Seyed Ali Ziaee2؛ Mahdi B. Khorasani3 | ||
| 1School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran. | ||
| 2Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran. | ||
| 3Amirkabir University of Technology, Tehran, Iran. | ||
| چکیده | ||
| The transportation sector accounts for a significant portion of global energy consumption and, gasoline is a major fuel consumed in road transport. On the other hand, the excessive consumption of gasoline can lead to an increase in unnecessary trips and road accidents. This study aims to determine the impact of macroscale factors on gasoline consumption. In this regard, we investigated the effect of gasoline price, oil reserves, and income level on gasoline consumption per capita in about 90 countries, including Iran, over a period of 17 years. Also, Rail and Air travel per capita and membership in the Organization for Economic Co-operation and Development (OECD) were considered as control variables. For this purpose, one of the classification techniques utilized in the area of data mining, Classification, and Regression Tree (CART), was employed. The variable importance measure (VIM) was calculated to quantify the association of each independent variable with the target variable. The results indicated that oil reserves, gasoline prices, and average income have a normalized significance of 100, 58.5, and 30.3 % respectively. Other variables do not have significant importance. So, higher per-capita gasoline consumption is exclusively involved in oil-rich countries such as Iran. Therefore, considering national oil reserves should be prioritized when comparing fuel consumption across world countries. Also, more expensive gasoline would relatively diminish its use. However, this effect of the gasoline price is mostly confirmed for countries with lower national oil reserves which often have higher prices than their counterparts. | ||
| کلیدواژه‌ها | ||
| Gasoline Consumption؛ Gasoline Price؛ Oil Reserves؛ Classification and Regression Tree (CART)؛ Variable Importance Measure (VIM) | ||
| مراجع | ||
|
[1] M. González-Torres, L. Pérez-Lombard, J. F. Coronel, I. R. Maestre, and D. Yan, "A review on buildings energy information: Trends, end-uses, fuels and drivers," Energy Reports, vol. 8, pp. 626-637, 2022.
[2] L. Chapman, “Transport and climate change: a review,” J Transp Geogr, vol. 15, no. 5, pp. 354–367, 2007.
[3] A. Tavakoli Kashani and zahra Sartibi, “Gasoline price, Gasoline consumption and road fatalities,” The 17th international conference on transportation and traffic engineering. Tehran, Iran, 2018. (In Persian)
[4] U. S. E. I. Administration, “Motor Gasoline consumption by country,” 2000-2016. 2019.
[5] P. J. Burke and S. Nishitateno, “Gasoline prices, gasoline consumption, and new-vehicle fuel economy: Evidence for a large sample of countries,” Energy Econ, vol. 36, pp. 363–370, 2013.
[6] P. J. Burke and S. Nishitateno, “Gasoline prices and road fatalities: International evidence,” Econ Inq, vol. 53, no. 3, pp. 1437–1450, 2015.
[7] H. H. Jafari and A. Baratimalayeri, “The crisis of gasoline consumption in the Iran’s transportation sector,” Energy Policy, vol. 36, no. 7, pp. 2536–2543, 2008.
[8] S. E. West and R. C. Williams III, “The cost of reducing gasoline consumption,” American Economic Review, vol. 95, no. 2, pp. 294–299, 2005.
[9] A. Tavakoli Kashani and Z. Sartibi, “Is There a Relationship Between Rail Transport and Road Fatalities?” Iranian Journal of Science and Technology, Transactions of Civil Engineering, pp. 1–10, 2022.
[10] H. Mahmood, N. Maalel, and M. S. Hassan, “Probing the energy-environmental Kuznets curve hypothesis in oil and natural gas consumption models considering urbanization and financial development in Middle East countries,” Energies (Basel), vol. 14, no. 11, p. 3178, 2021.
[11] A. T. Kashani and A. S. Mohaymany, “Analysis of the traffic injury severity on two-lane, two-way rural roads based on classification tree models,” Saf Sci, vol. 49, no. 10, pp. 1314–1320, 2011.
[12] A. Tavakoli Kashani, R. Rabieyan, and M. M. Besharati, “A data mining approach to investigate the factors influencing the crash severity of motorcycle pillion passengers,” J Safety Res, vol. 51, pp. 93–98, Dec. 2014, doi: 10.1016/j.jsr.2014.09.004.
[13] S. Krishnaveni and M. Hemalatha, “A perspective analysis of traffic accident using data mining techniques,” Int J Comput Appl, vol. 23, no. 7, pp. 40–48, 2011.
[14] L. Li, S. Shrestha, and G. Hu, “Analysis of road traffic fatal accidents using data mining techniques,” in 2017 IEEE 15th International Conference on Software Engineering Research, Management and Applications (SERA), 2017, pp. 363–370.
[15] German Agency for International Cooperation (GIZ), “International Fuel Prices.”
[16] Lior Rokach and Oded Maimon, Data mining with decision trees: theory and applications. 2015.
[17] D. Delen, L. Tomak, K. Topuz, and E. Eryarsoy, “Investigating injury severity risk factors in automobile crashes with predictive analytics and sensitivity analysis methods,” J Transp Health, vol. 4, pp. 118–131, Mar. 2017, doi: 10.1016/j.jth.2017.01.009.
[18] L.-Y. Chang and H.-W. Wang, “Analysis of traffic injury severity: An application of non-parametric classification tree techniques,” Accid Anal Prev, vol. 38, no. 5, pp. 1019–1027, Sep. 2006, doi: 10.1016/j.aap.2006.04.009.
[19] X. Wen, Y. Xie, L. Jiang, Z. Pu, and T. Ge, “Applications of machine learning methods in traffic crash severity modelling: current status and future directions,” Transp Rev, vol. 41, no. 6, pp. 855–879, Nov. 2021, doi: 10.1080/01441647.2021.1954108.
[20] P. Treeratpituk and C. L. Giles, “Disambiguating authors in academic publications using random forests,” in Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries, Jun. 2009, pp. 39–48. doi: 10.1145/1555400.1555408.
[21] United States Energy Information Administration (EIA), “Open Data.”
[22] International Civil Aviation Organization (ICAO), “Statistics.”
[23] International Union of Railways (UIC), “Statistics.”
[24] World Bank, “World Bank Open Data.”
[25] Organisation for Economic Co-operation and Development (OECD), “OECD Data.”
[26] D. Steinberg and M. Golovnya, “CART 6.0 user’s guide,” Salford Systems, San Diego, CA, 2007.
[27] A. V. Veettil and A. K. Mishra, "Quantifying thresholds for advancing impact-based drought assessment using classification and regression tree (CART) models," Journal of Hydrology, vol. 625, p. 129966, 2023. | ||
|
آمار تعداد مشاهده مقاله: 224 تعداد دریافت فایل اصل مقاله: 263 |
||