Prediction of Specific Fuel Consumption of 60 HP 2WD Tractor Using Artificial Neural Networks
Abstract
Keywords
References
- Taşbaş, H., Aygül, A., İlban, B., Civciv, M. Tarım ve Köyişleri Bakanlığı Tarım Alet ve Makineleri Test Merkezi Müdürlüğü. Tarım Traktörlerinin OECD Test Koduna (Code 2) Göre Per-formans Değerleri. 2003. 1999-2002, Ankara
- Öğüt, H. Tarım Traktörleri. Selçuk Üniversitesi Ziraat Fakültesi Yayınları. 1995. No: 23, Konya.
- Taylor, J. H. Energy savings through improved tractive effi-ciency. 1981. ASAE Publ.; (United States), 4(CONF-8009144-(Vol. 2)).
- Karparvarfard, S. H., Rahmanian-Koushkaki, H. Development of a Fuel Consumption Equation: Test Case for a Tractor Chisel-ploughing in a Clay Loam Soil. Biosystems Engineering. 2015. 130, 23-33. Sabancı, A. Tarım Traktörleri. Çukurova Üniversitesi Ziraat Fakültesi Genel Yayın No:46. Ders Kitapları Yayın No: 9.1993. Adana.
- Kadayıfçılar, S. Tarım Traktörlerinin Deney Sonuçlarının İrdelenmesi. Tarımsal Mekanizasyon 14. Ulusal Kongresi. 1992. Samsun.
- Burt, E. C., Bailey, A. C. Load and Inflation Pressure Effects on Tires. Transactions of The ASAE 25. 1982. (4):881-884. Damanauskas, V., Janulevičius, A., Pupinis, G. Influence of Extra Weight and Tire Pressure on Fuel Consumption at Normal Tractor Slippage. Journal of Agricultural Science. 2015. 7(2), 55-67. Battiato, A., Diserens, E. Influence of Tyre Inflation Pressure and Wheel Load on The Traction Performance of a 65 kW MFWD Tractor on a Cohesive Soil. Journal of Agricultural Science. 2013. 5(8), 197.
- Battiato, A., Diserens, E. Influence of Soil on The Traction Performance of a 65 kW MFWD Tractor. Journal of Agricultural Science. 2019. 11(17), 11.
- Ekinci, Ş., Çarman, K., Kahramanlı, H. Investigation and Modeling of The Tractive Performance of Radial Tires Using Off-road Vehicles. Energy. 2015. 93, 1953-1963. Parlak, A., Islamoglu, Y., Yasar, H., Egrisogut, A. Appli-cation of Artificial Neural Network to Predict Specific Fuel Consumption and Exhaust Temperature for a Diesel Engine. Applied Thermal Engineering. 2006. 26(8-9), 824-828.
Details
Primary Language
English
Subjects
Mechanical Engineering
Journal Section
Research Article
Publication Date
December 31, 2021
Submission Date
October 15, 2021
Acceptance Date
December 24, 2021
Published in Issue
Year 2021 Volume: 5 Number: 4
Cited By
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