2023
DOI: 10.32604/csse.2023.029017
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Q-Learning-Based Pesticide Contamination Prediction in Vegetables and Fruits

Abstract: Pesticides have become more necessary in modern agricultural production. However, these pesticides have an unforeseeable long-term impact on people's wellbeing as well as the ecosystem. Due to a shortage of basic pesticide exposure awareness, farmers typically utilize pesticides extremely close to harvesting. Pesticide residues within foods, particularly fruits as well as veggies, are a significant issue among farmers, merchants, and particularly consumers. The residual concentrations were far lower than these… Show more

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Cited by 2 publications
(1 citation statement)
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“…The problem that the training efficiency of Reinforcement Learning Agent is slow and it is easy to fall into local optimal [32,33] is solved. At the same time, the error correction of prediction results [34,35] is carried out to improve the prediction accuracy of the model and provide a new way of thinking for the field of lake eutrophication prediction.…”
Section: Introductionmentioning
confidence: 99%
“…The problem that the training efficiency of Reinforcement Learning Agent is slow and it is easy to fall into local optimal [32,33] is solved. At the same time, the error correction of prediction results [34,35] is carried out to improve the prediction accuracy of the model and provide a new way of thinking for the field of lake eutrophication prediction.…”
Section: Introductionmentioning
confidence: 99%