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Conference Papers Year : 2016

Environmental Impact on Predicting Olive Fruit Fly Population Using Trap Measurements

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1
Romanos Kalamatianos
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  • PersonId : 1012054
Katia Kermanidis
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  • PersonId : 992337
Markos Avlonitis
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  • PersonId : 1008284
Ioannis Karydis
  • Function : Author
  • PersonId : 992354

Abstract

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.
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Dates and versions

hal-01557647 , version 1 (06-07-2017)

Licence

Attribution - CC BY 4.0

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Romanos Kalamatianos, Katia Kermanidis, Markos Avlonitis, Ioannis Karydis. Environmental Impact on Predicting Olive Fruit Fly Population Using Trap Measurements. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. pp.180-190, ⟨10.1007/978-3-319-44944-9_16⟩. ⟨hal-01557647⟩
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