Environmental Impact on Predicting Olive Fruit Fly Population Using Trap Measurements

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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Communication dans un congrès
Lazaros Iliadis; Ilias Maglogiannis. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. IFIP Advances in Information and Communication Technology, AICT-475, pp.180-190, 2016, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-319-44944-9_16〉
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Romanos Kalamatianos, Katia Kermanidis, Markos Avlonitis, Ioannis Karydis. Environmental Impact on Predicting Olive Fruit Fly Population Using Trap Measurements. Lazaros Iliadis; Ilias Maglogiannis. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. IFIP Advances in Information and Communication Technology, AICT-475, pp.180-190, 2016, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-319-44944-9_16〉. 〈hal-01557647〉

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