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Displaying 1 - 5 of 5 Publications- … gas (GHG) emission, the application of machine-learning (ML) models can help reduce the requirement of intensive … the accuracy of predictions. Here, we developed a novel ML model that integrated a hybrid Prophet-ANN and snapshot …AuthorsS.N. Ferdous, J.P. Ahire, R. Bergman, L. Xin, E. Blanc-Betes, Z. Zhang, J. WangKeywordsSourceJournal: Ecological InformaticsYear2025
- … Here, we leveraged an ensemble of five machine learning (ML) models and multiple satellite-based observations to … learning is a meta-approach that combines multiple ML predictions to improve accuracy, robustness, and … performance. We found that the optimized ensemble ML well reproduced annual dynamics of global burned area (R 2 …AuthorsYulong Zhang, Jiafu Mao, Daniel M. Ricciuto, Mingzhou Jin, Yan Yu, Xiaoying Shi, Stan Wullschleger, Rongyun Tang, Jicheng LiuKeywordsSourceScience of Remote SensingYear2023
- … science and engineering has mainly utilized the classic model development methods, such as principal component … limited studies conducted on evaluating machine learning (ML) models, and specifically, artificial neural networks …AuthorsVahid Nasir, Syed Danish Ali, Ahmad Mohammadpanah, Sameen Raut, Mohamad Nabavi, Joseph Dahlen, Laurence SchimleckKeywordsSourceWood and Fiber ScienceYear2023
- … We proposed a robust deep ensemble machine learning(ML) model to estimate soil sustainability indicators [i.e., … management practices. The results showed that proposed ML models are having very high predictability [SEF,R 2 = …AuthorsSyeda Nyma Ferdous, Xin Li, Kamalakanta Sahoo, Richard BergmanKeywordsSourceBioresource Technology ReportsYear2023
Towards the Modeling and Prediction of the Yield of Oilseed Crops: A Multi-Machine Learning Approach
… of agro-traits. Here, multiple machine learning (ML) techniques are employed to predict sesame ( Sesamum … yields (SSY) using agro-morphological features. Various ML models were applied, coupled with the PCA (principal …AuthorsMahdieh Parsaeian, Mohammad Rahimi, Abbas Rohani, Shaneka S. LawsonSourceAgricultureYear2022