About: Thrips (Thysanoptera) identification using artificial neural networks

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	We 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: Aeolothrips Haliday (Aeolothripidae), Chirothrips Haliday, Dendrothrips Uzel, and Limothrips Haliday (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. We 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: Aeolothrips Haliday (Aeolothripidae), Chirothrips Haliday, Dendrothrips Uzel, and Limothrips Haliday (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. (en)
Title	Thrips (Thysanoptera) identification using artificial neural networks Thrips (Thysanoptera) identification using artificial neural networks (en)
skos:prefLabel	Thrips (Thysanoptera) identification using artificial neural networks Thrips (Thysanoptera) identification using artificial neural networks (en)
skos:notation	RIV/00216224:14310/08:00027185!RIV13-MSM-14310___
http://linked.open...avai/riv/aktivita	S Z
http://linked.open...avai/riv/aktivity	S, Z(MK00009486201), Z(MSM0021622416)
http://linked.open...iv/cisloPeriodika	4
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Havel, Josef Vaňhara, Jaromír
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Masarykova univerzita / Přírodovědecká fakulta
http://linked.open...dnocenehoVysledku	400017
http://linked.open...ai/riv/idVysledku	RIV/00216224:14310/08:00027185
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	ANN; Thrips; identification (en)
http://linked.open.../riv/klicoveSlovo	ANN Thrips identification
http://linked.open...odStatuVydavatele	GB - Spojené království Velké Británie a Severního Irska
http://linked.open...ontrolniKodProRIV	[0ED2748D70D8]
http://linked.open...i/riv/nazevZdroje	Bulletin of Entomological Research
http://linked.open...in/vavai/riv/obor	EG
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	5 (xsd:int)
http://linked.open...UplatneniVysledku	2008
http://linked.open...v/svazekPeriodika	98
http://linked.open...iv/tvurceVysledku	Fedor, Peter Havel, Josef Malenovský, Igor Vaňhara, Jaromír Sierka, W.
http://linked.open...ain/vavai/riv/wos	000260173700002
http://linked.open...n/vavai/riv/zamer	Vytváření pramenné báze a studium přírodních procesů probíhajících v širší oblasti styků karpatské, hercynské a panonské oblasti Diversity of Biotic Communities and Populations: Causal Analysis of variation in space and time
issn	0007-4853
number of pages	11 (xsd:int)
http://localhost/t...ganizacniJednotka	14310

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