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Showing 1 to 1 of 1 for “"fertilizer, agriculture, multiobjective, evolutionary, algorithms, RZWQM2"”.

  1. Quantifying the agronomic and water quality tradeoffs of fertilizer management with multiobjective evolutionary algorithms

    When combined with agricultural systems models, multiobjective evolutionary algorithms (MOEAs) can efficiently quantify optimal tradeoffs (Pareto fronts) among conflicting economic and environmental objectives to help farmers identify compromise decision alternatives. Realizing the potential of …

    uiuc Repository record for Quantifying the agronomic and water quality tradeoffs of fertilizer management with multiobjective evolutionary algorithms (opens in a new tab)