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A Cumulative Training Approach to Schistosomiasis Vector Density Prediction Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Environmental Impact on Predicting Olive Fruit Fly Population Using Trap Measurements

Authors : Romanos Kalamatianos, Katia Kermanidis, Markos Avlonitis, Ioannis Karydis

Published in: Artificial Intelligence Applications and Innovations

Publisher: Springer International Publishing

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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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Footnotes
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Metadata
Title
Environmental Impact on Predicting Olive Fruit Fly Population Using Trap Measurements
Authors
Romanos Kalamatianos
Katia Kermanidis
Markos Avlonitis
Ioannis Karydis
Copyright Year
2016
Book
Artificial Intelligence Applications and Innovations

Print ISBN: 978-3-319-44943-2

Electronic ISBN: 978-3-319-44944-9

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-44944-9_16

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