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- Title
Thrips (Thysanoptera) identification using artificial neural networks.
- Abstract
AbstractWe studied the use of a supervised artificial neural network (ANN) model for semi-automated identification of 18 common European species of Thysanoptera from four genera: AeolothripsHaliday (Aeolothripidae), ChirothripsHaliday, DendrothripsUzel, and LimothripsHaliday (all Thripidae). As input data, we entered 17 continuous morphometric and two qualitative two-state characters measured or determined on different parts of the thrips body (head, pronotum, forewing and ovipositor) and the sex. Our experimental data set included 498 thrips specimens. A relatively simple ANN architecture (multilayer perceptrons with a single hidden layer) enabled a 97% correct simultaneous identification of both males and females of all the 18 species in an independent test. This high reliability of classification is promising for a wider application of ANN in the practice of Thysanoptera identification.
- Subjects
THRIPS; INSECTS; PHLAEOTHRIPIDAE; THRIPIDAE
- Publication
Bulletin of Entomological Research, 2008, Vol 98, Issue 5, p437
- ISSN
0007-4853
- Publication type
Article
- DOI
10.1017/S0007485308005750