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Krzysztof Drachal and Michal Pawlowski
This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities? prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventional approa...
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Ganeshchandra Mallya, Mohamed M. Hantush and Rao S. Govindaraju
Effective water quality management and reliable environmental modeling depend on the availability, size, and quality of water quality (WQ) data. Observed stream water quality data are usually sparse in both time and space. Reconstruction of water quality...
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Subhrajit Satpathy, Dipendra Shahi, Brayden Blanchard, Michael Pontif, Kenneth Gravois, Collins Kimbeng, Anna Hale, James Todd, Atmakuri Rao and Niranjan Baisakh
Sugarcane (Saccharum spp.) is an important perennial grass crop for both sugar and biofuel industries. The Louisiana sugarcane breeding program is focused on improving sugar yield by incrementally increasing genetic gain. With the advancement in genotypi...
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Enas Elgeldawi, Awny Sayed, Ahmed R. Galal and Alaa M. Zaki
Machine learning models are used today to solve problems within a broad span of disciplines. If the proper hyperparameter tuning of a machine learning classifier is performed, significantly higher accuracy can be obtained. In this paper, a comprehensive ...
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