[1] Giakoumis EG. Driving and Engine Cycles. Cham: Springer International Publishing; 2017.
doi: 10.1007/978-3-319-49034-2
[2] BARLOW TJ, Latham S, McCrae IS, Boulter PG. A reference book of driving cycles for use in the measurement of road vehicle emissions. Proj Rep. 2009; Version 3.
[3] Rdig W. Environmental Policy-Making in Britain, Germany and the European Union: The Europeanisation of Air and Water Pollution Control. By Rdiger K. W. Wurzel. Manchester: Manchester University Press, 2002. 304p. Perspect Polit. 2004;2:210–1.
doi: 10.1017/S1537592704280707
[4] Kuhler M, Karstens D. Improved Driving Cycle for Testing Automotive Exhaust Emissions. Proc. Inst. clean air Conf. Pap., vol. 1, 1978, p. 157–63.
doi: 10.4271/780650
[5] Watson HC. Vehicle driving patterns and measurement methods for energy and emissions assessment .1978.
[6] Standard ISO, ISO BS. Reciprocating internal combustion engines—Exhaust emission measurement. 2006.
[7] Kotus M, Pexa M, Kubín K. MODELLING OF NON-ROAD TRANSIENT CYCLE. J Cent Eur Agric. 2013;14:1281–94.
doi: 10.5513/JCEA01/14.4.1344
[8] Wisell T, Jerksjö M, Hult C, Lindgren M. Fuel and Technology Alternatives in Non-Road Engines. Annex 50 IEA Adv Mot Fuels Technol Collab Program. 2019.
[9] Hussein Abbas Jebur. A review: Machine relationship with the tractor and its effect on the productivity and compaction of agricultural soil. Univ Thi-Qar J Agric Res. 2023;12:22–43.
doi: 10.54174/utjagr.v12i1.237
[10] Mateo‐Marín N, Bosch‐Serra ÀD, Molina MG, Poch RM. Impacts of tillage and nutrient management on soil porosity trends in dryland agriculture. Eur J Soil Sci. 2022;73:1–17.
doi: 10.1111/ejss.13139
[11] D’Acqui LP, Certini G, Cambi M, Marchi E. Machinery’s impact on forest soil porosity. J Terramechanics. 2020;91:65–71.
doi: 10.1016/j.jterra.2020.05.002
[12] Moosavian A, Abdolmaleki S, Rezaei M, Nejat M. Driving Cycle Extraction of Tehran City’s West Region for a Car with Turbocharged Engine using Microtrip Clustering Method. 2019:3–12. [In Persian]
[13] Masih-Tehrani M, Ebrahimi-Nejad S. Hybrid Genetic Algorithm and Linear Programming for Bulldozer Emissions and Fuel-Consumption Management Using Continuously Variable Transmission. J Constr Eng Manag. 2018;144:2–10.
doi: 10.1061/(asce)co.1943-7862.0001490
[14] Karimi G, Masih-Tehrani M, Pourbafarani Z. Development of Wheel Loader Duty Cycle Using Hybrid Markov Chain and Genetic Algorithm. SAE Int J Commer Veh. 2021;15:02-14-04–0034.
doi: 10.4271/02-14-04-0034
[15] Yang L, Tian W, Zhai W, Wang X, Chen Z, Wen L, et al. Behavior recognition and fuel consumption prediction of tractor sowing operations using smartphone. Int J Agric Biol Eng. 2022;15:154–62.
doi: 10.25165/j.ijabe.20221504.7454
[16] Topić J, Škugor B, Deur J. Neural Network-Based Prediction of Vehicle Fuel Consumption Based on Driving Cycle Data. Sustainability. 2022;14:744.
doi: 10.3390/su14020744
[17] Asadi A, Azadi M, Khalesi MH, Ashkan S. Investigating the effects of geographics climate on the characteristics of statistical data and driving cycle. 2023;70:37–65.
doi: 10.22034/ER.2023.2009114.1013 [In Persian]
[18] Wu Y, Zhang W, Zhang L, Qiao Y, Yang J, Cheng C. A Multi-Clustering Algorithm to Solve Driving Cycle Prediction Problems Based on Unbalanced Data Sets: A Chinese Case Study. Sensors 2020;20:2448.
doi: 10.3390/s20092448
[19] Rapalis P, Lebedevas S, Mickevičienė R. Mathematical Modelling of Diesel Engine Operational Performance Parameters in Transient Modes. Pomorstvo. 2018;32:165–72.
doi: 10.31217/p.32.2.1
[20] Ye X, Lu J, Tian S, Zhao Z, Lv Q, Zhang Z. Research on Driving Cycle Recognition Strategy Based on Machine Learning. Lect. Notes Electr. Eng., vol. 1016 LNEE, 2023, p. 140–51.
doi: 10.1007/978-981-99-1027-4_15
[21] Khodabakhshian M, Feng L, Wikander J. Improvement of Fuel Efficiency and Drivability Using Simple Prediction for Gear Changing. IFAC Proc Vol. 2013;46:518–23.
doi: 10.3182/20130904-4-JP-2042.00050
[22] Pandey V, van Dooren S, Ritzmann J, Pla B, Onder C. Variable smoothing of optimal diesel engine calibration for improved performance and drivability during transient operation. Int J Engine Res. 2021;22:1888–95.
doi: 10.1177/1468087420918801
[23] Feng R, Chen K, Sun Z, Hu X, Li G, Wang S, et al. A comparative study on the energy flow of a hybrid heavy truck between AMT and MT shift mode under local driving test cycle. Energy Convers Manag. 2022;256:115359.
doi: 10.1016/j.enconman.2022.115359
[24] Wang X, Zhao Y, Li W. Recognition of Commercial Vehicle Driving Cycles Based on Multilayer Perceptron Model. Sustainability. 2023;15:2644.
doi: 10.3390/su15032644
[25] Stoel B. Use of artificial intelligence in imaging in rheumatology – current status and future perspectives. RMD Open. 2020;6:e001063.
doi: 10.1136/rmdopen-2019-001063
