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Filtering by: Subject Environmental sciences -- Computer programs Remove constraint Subject: Environmental sciences -- Computer programs Academic Affiliation Biological and Ecological Engineering Remove constraint Academic Affiliation: Biological and Ecological Engineering

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  • Development of a Statistical Emulator of US Crop Yields via a Deep Neural Network Approach

    Creator:
    Proctor, Kyle W.
    Abstract:
    Agricultural systems are inherently complex; understanding these systems requires knowledge of climatology, plant physiology, soil physics, economics, and the human psychology of the farmers themselves. Decision support tools strive to leverage existing data to help guide stakeholders towards the best policies and practices for their situation. Quantitative crop simulation models...
    Resource Type:
    Masters Thesis
    Full Text:
    degree of Master of Science in Biological and Ecological Engineering presented on March 2, 2021