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Environmental Impact on Predicting Olive Fruit Fly Population Using Trap Measurements

Domaine:

agriculture

Type de record:

paper
Créateur:
KalKerAvlKar
Éditeur:
IonLazIliTC
Éditeur:
CCSD
Hôte:avatar
Part 4: Environmental AI Modeling (ENAIM) International audience Olive fruit fly trap measurements are used as one of the indicators for olive grove infestation, and therefore, as a consultation tool on spraying parameters. In this paper, machine learning techniques are used to predict the next olive fruit fly trap measurement, given as input environmental parameters and knowledge of previous trap measurements. Various classification algorithms are employed and applied to different environmental settings, in extensive comparative experiments, in order to detect the impact of the latter on olive fruit fly population prediction.

Visit

inria.hal.science

Tags

Support vector machinesRandom forestsDecision treesNearest neighborsNaive bayesClassificationPopulation predictionMachine learningOlive fruit fly[INFO]Computer Science [cs]

Licenses

http://creativecommons.org/licenses/by/info:eu-repo/semantics/OpenAccess

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