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Determination and modelling of energy consumption in wheat production using neural networks: “A case study in Canterbury province, New Zealand”

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  1. Van linden, Veerle & Herman, Lieve, 2014. "A fuel consumption model for off-road use of mobile machinery in agriculture," Energy, Elsevier, vol. 77(C), pages 880-889.
  2. Khoshnevisan, Benyamin & Rafiee, Shahin & Omid, Mahmoud & Mousazadeh, Hossein & Shamshirband, Shahaboddin & Hamid, Siti Hafizah Ab, 2015. "Developing a fuzzy clustering model for better energy use in farm management systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 27-34.
  3. Jamali, Mohsen & Soufizadeh, Saeid & Yeganeh, Bijan & Emam, Yahya, 2021. "A comparative study of irrigation techniques for energy flow and greenhouse gas (GHG) emissions in wheat agroecosystems under contrasting environments in south of Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
  4. Venkatesh Paramesh & Parveen Kumar & Ranjan Parajuli & Rosa Francaviglia & Kallakeri Kannappa Manohara & Vadivel Arunachalam & Trivesh Mayekar & Sulekha Toraskar, 2023. "A Life Cycle Assessment of Rice–Rice and Rice–Cowpea Cropping Systems in the West Coast of India," Land, MDPI, vol. 12(2), pages 1-14, February.
  5. Muhammad N. Ashraf & Muhammad H. Mahmood & Muhammad Sultan & Narges Banaeian & Muhammad Usman & Sobhy M. Ibrahim & Muhammad U. B. U. Butt & Muhammad Waseem & Imran Ali & Aamir Shakoor & Zahid M. Khan, 2020. "Investigation of Input and Output Energy for Wheat Production: A Comprehensive Study for Tehsil Mailsi (Pakistan)," Sustainability, MDPI, vol. 12(17), pages 1-22, August.
  6. Khoshnevisan, Benyamin & Rafiee, Shahin & Omid, Mahmoud & Yousefi, Marziye & Movahedi, Mehran, 2013. "Modeling of energy consumption and GHG (greenhouse gas) emissions in wheat production in Esfahan province of Iran using artificial neural networks," Energy, Elsevier, vol. 52(C), pages 333-338.
  7. Benedetti, Miriam & Cesarotti, Vittorio & Introna, Vito & Serranti, Jacopo, 2016. "Energy consumption control automation using Artificial Neural Networks and adaptive algorithms: Proposal of a new methodology and case study," Applied Energy, Elsevier, vol. 165(C), pages 60-71.
  8. Lan Ma & Fangping Xie & Dawei Liu & Xiushan Wang & Zhanfeng Zhang, 2023. "An Application of Artificial Neural Network for Predicting Threshing Performance in a Flexible Threshing Device," Agriculture, MDPI, vol. 13(4), pages 1-15, March.
  9. Vlontzos, G. & Pardalos, P.M., 2017. "Assess and prognosticate green house gas emissions from agricultural production of EU countries, by implementing, DEA Window analysis and artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 155-162.
  10. Di Lullo, G. & Oni, A.O. & Kumar, A., 2023. "The development of complex engineering models using artificial neural network-based proxy models for life cycle assessments of energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
  11. Soltani, Afshin & Rajabi, M.H. & Zeinali, E. & Soltani, Elias, 2013. "Energy inputs and greenhouse gases emissions in wheat production in Gorgan, Iran," Energy, Elsevier, vol. 50(C), pages 54-61.
  12. Jan Svanberg & Tohid Ardeshiri & Isak Samsten & Peter Öhman & Presha E. Neidermeyer & Tarek Rana & Natalia Semenova & Mats Danielson, 2022. "Corporate governance performance ratings with machine learning," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(1), pages 50-68, January.
  13. Olanrewaju, O.A. & Jimoh, A.A. & Kholopane, P.A., 2012. "Integrated IDA–ANN–DEA for assessment and optimization of energy consumption in industrial sectors," Energy, Elsevier, vol. 46(1), pages 629-635.
  14. Hafiz Muhammad Abrar Ilyas & Majeed Safa & Alison Bailey & Sara Rauf & Marvin Pangborn, 2019. "The Carbon Footprint of Energy Consumption in Pastoral and Barn Dairy Farming Systems: A Case Study from Canterbury, New Zealand," Sustainability, MDPI, vol. 11(17), pages 1-15, September.
  15. Olanrewaju, O.A. & Jimoh, A.A. & Kholopane, P.A., 2013. "Assessing the energy potential in the South African industry: A combined IDA-ANN-DEA (Index Decomposition Analysis-Artificial Neural Network-Data Envelopment Analysis) model," Energy, Elsevier, vol. 63(C), pages 225-232.
  16. Uzlu, Ergun & Akpınar, Adem & Özturk, Hasan Tahsin & Nacar, Sinan & Kankal, Murat, 2014. "Estimates of hydroelectric generation using neural networks with the artificial bee colony algorithm for Turkey," Energy, Elsevier, vol. 69(C), pages 638-647.
  17. Yildizhan, Hasan, 2018. "Energy, exergy utilization and CO2 emission of strawberry production in greenhouse and open field," Energy, Elsevier, vol. 143(C), pages 417-423.
  18. Yuan, Shen & Peng, Shaobing & Wang, Dong & Man, Jianguo, 2018. "Evaluation of the energy budget and energy use efficiency in wheat production under various crop management practices in China," Energy, Elsevier, vol. 160(C), pages 184-191.
  19. Du, Xiangbei & He, Wenchang & Gao, Shangqin & Liu, Dong & Wu, Wenge & Tu, Debao & Kong, Lingcong & Xi, Min, 2022. "Raised bed planting increases economic efficiency and energy use efficiency while reducing the environmental footprint for wheat after rice production," Energy, Elsevier, vol. 245(C).
  20. Yeo, In-Ae & Yee, Jurng-Jae, 2014. "A proposal for a site location planning model of environmentally friendly urban energy supply plants using an environment and energy geographical information system (E-GIS) database (DB) and an artifi," Applied Energy, Elsevier, vol. 119(C), pages 99-117.
  21. Kaur, Karman & Prasad, Narayan & Prasad, Narayan, 2021. "Modelling Input Energy Used in Wheat Production in India Using Artificial Neural Network," 2021 Conference, August 17-31, 2021, Virtual 315051, International Association of Agricultural Economists.
  22. Naseri, Hakim & Parashkoohi, Mohammad Gholami & Ranjbar, Iraj & Zamani, Davood Mohammad, 2021. "Energy-economic and life cycle assessment of sugarcane production in different tillage systems," Energy, Elsevier, vol. 217(C).
  23. Macedo, M.N.Q. & Galo, J.J.M. & de Almeida, L.A.L. & de C. Lima, A.C., 2015. "Demand side management using artificial neural networks in a smart grid environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 128-133.
  24. Kazemi, Hossein & Kamkar, Behnam & Lakzaei, Somayeh & Badsar, Meysam & Shahbyki, Malihe, 2015. "Energy flow analysis for rice production in different geographical regions of Iran," Energy, Elsevier, vol. 84(C), pages 390-396.
  25. Kuruguntu Mohan Krithika & Nachimuthu Maheswari & Manickam Sivagami, 2022. "Models for feature selection and efficient crop yield prediction in the groundnut production," Research in Agricultural Engineering, Czech Academy of Agricultural Sciences, vol. 68(3), pages 131-141.
  26. Taheri-Rad, Alireza & Khojastehpour, Mehdi & Rohani, Abbas & Khoramdel, Surur & Nikkhah, Amin, 2017. "Energy flow modeling and predicting the yield of Iranian paddy cultivars using artificial neural networks," Energy, Elsevier, vol. 135(C), pages 405-412.
  27. Jalali, Vahidreza & Asadi Kapourchal, Safoora & Homaee, Mehdi, 2017. "Evaluating performance of macroscopic water uptake models at productive growth stages of durum wheat under saline conditions," Agricultural Water Management, Elsevier, vol. 180(PA), pages 13-21.
  28. Buratti, C. & Barbanera, M. & Palladino, D., 2014. "An original tool for checking energy performance and certification of buildings by means of Artificial Neural Networks," Applied Energy, Elsevier, vol. 120(C), pages 125-132.
  29. Hamed Rafiee & Milad Aminizadeh & Elham Mehrparvar Hosseini & Hanane Aghasafari & Ali Mohammadi, 2022. "A Cluster Analysis on the Energy Use Indicators and Carbon Footprint of Irrigated Wheat Cropping Systems," Sustainability, MDPI, vol. 14(7), pages 1-19, March.
  30. Binoy Kumar Show & Suraj Panja & Richik GhoshThakur & Aman Basu & Apurba Koley & Anudeb Ghosh & Kalipada Pramanik & Shibani Chaudhury & Amit Kumar Hazra & Narottam Dey & Andrew B. Ross & Srinivasan Ba, 2023. "Optimisation of Anaerobic Digestate and Chemical Fertiliser Application to Enhance Rice Yield—A Machine-Learning Approach," Sustainability, MDPI, vol. 15(18), pages 1-13, September.
  31. Khoshnevisan, Benyamin & Rafiee, Shahin & Omid, Mahmoud & Mousazadeh, Hossein & Rajaeifar, Mohammad Ali, 2014. "Application of artificial neural networks for prediction of output energy and GHG emissions in potato production in Iran," Agricultural Systems, Elsevier, vol. 123(C), pages 120-127.
  32. Khoshnevisan, Benyamin & Shariati, Hanifreza Motamed & Rafiee, Shahin & Mousazadeh, Hossein, 2014. "Comparison of energy consumption and GHG emissions of open field and greenhouse strawberry production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 316-324.
  33. Muhammad N. Ashraf & Muhammad H. Mahmood & Muhammad Sultan & Redmond R. Shamshiri & Sobhy M. Ibrahim, 2021. "Investigation of Energy Consumption and Associated CO 2 Emissions for Wheat–Rice Crop Rotation Farming," Energies, MDPI, vol. 14(16), pages 1-18, August.
  34. Julio R. G mez Sarduy & Percy R. Viego Felipe & Yamile D az Torres & Mario A. lvarez-Guerra Plascencia & Vladimir Sousa Santos & Dries Haeseldonckx, 2018. "A New Energy Performance Indicator for Energy Management System of a Wheat Mill Plant," International Journal of Energy Economics and Policy, Econjournals, vol. 8(4), pages 324-330.
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