首页|Findings on Machine Learning Reported by Investigators at University of Lorraine (Predicting the Abundances of Aphids and Their Natural Enemies In Cereal Crops: Machine-learning Versus Linear Models)

Findings on Machine Learning Reported by Investigators at University of Lorraine (Predicting the Abundances of Aphids and Their Natural Enemies In Cereal Crops: Machine-learning Versus Linear Models)

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Investigators publish new report on Machine Learning. According to news reporting out of Nancy, France, by NewsRx editors, research stated, “Predicting the effects of crop management and landscape structure on biological pest control is a key challenge for implementing innovative pest management systems. Here, we compare the performances of two machine-learning methods (regression trees and random forests) with those of linear models in predicting cereal aphid abundance, parasitism, and natural enemies.” Financial support for this research came from CASDAR ‘ARENA’ Program from the French ministry of Agriculture and Food.

NancyFranceEuropeCyborgsEmerging TechnologiesMachine LearningUniversity of Lorraine

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Feb.1)
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