Artificial Intelligence Applications and Innovations 12th IFIP WG 12.5 International Conference and Workshops, AIAI 2016 Thessaloniki, Greece, September 16–18, 2016
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.
https://hal.inria.fr/hal-01557647
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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⟩
