Towards the Modeling and Prediction of the Yield of Oilseed Crops: A Multi-Machine Learning Approach
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- Khalied Albarrak & Yonis Gulzar & Yasir Hamid & Abid Mehmood & Arjumand Bano Soomro, 2022. "A Deep Learning-Based Model for Date Fruit Classification," Sustainability, MDPI, vol. 14(10), pages 1-16, May.
- Sudret, Bruno, 2008. "Global sensitivity analysis using polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 964-979.
- Vinushi Amaratunga & Lasini Wickramasinghe & Anushka Perera & Jeevani Jayasinghe & Upaka Rathnayake, 2020. "Artificial Neural Network to Estimate the Paddy Yield Prediction Using Climatic Data," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-11, July.
- Mousavi-Avval, Seyed Hashem & Shah, Ajay, 2021. "Techno-economic analysis of hydroprocessed renewable jet fuel production from pennycress oilseed," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
- Masako Ikegami & Zijian Wang, 2021. "Does energy aid reduce CO2 emission intensities in developing countries?," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 10(4), pages 343-358, October.
- Soltanali, Hamzeh & Nikkhah, Amin & Rohani, Abbas, 2017. "Energy audit of Iranian kiwifruit production using intelligent systems," Energy, Elsevier, vol. 139(C), pages 646-654.
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- Hung Vo Thanh & Sajad Ebrahimnia Taremsari & Benyamin Ranjbar & Hossein Mashhadimoslem & Ehsan Rahimi & Mohammad Rahimi & Ali Elkamel, 2023. "Hydrogen Storage on Porous Carbon Adsorbents: Rediscovery by Nature-Derived Algorithms in Random Forest Machine Learning Model," Energies, MDPI, vol. 16(5), pages 1-19, February.
- Rahimi, Mohammad & Mashhadimoslem, Hossein & Vo Thanh, Hung & Ranjbar, Benyamin & Safarzadeh Khosrowshahi, Mobin & Rohani, Abbas & Elkamel, Ali, 2023. "Yield prediction and optimization of biomass-based products by multi-machine learning schemes: Neural, regression and function-based techniques," Energy, Elsevier, vol. 283(C).
- Baoshan Wang & Qingxi Liao & Lei Wang & Caixia Shu & Mei Cao & Wenbin Du, 2023. "Design and Test of Air-Assisted Seed-Guiding Device of Precision Hill-Seeding Centralized Seed-Metering Device for Sesame," Agriculture, MDPI, vol. 13(2), pages 1-21, February.
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Keywords
agro-morphological; data-driven; machine learning; seed yield; sensitivity analysis;All these keywords.
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