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Supervised classification of plant communities with artificial neural networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F05%3A00012592" target="_blank" >RIV/00216224:14310/05:00012592 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Supervised classification of plant communities with artificial neural networks

  • Original language description

    Questions: Are artificial neural networks useful for the automatic assignment of species composition records from vegetation plots to a priori established classes (vegetation units)? Is the assignment more accurate (1) if the classes are defined by numerical classification rather than by expert-based classification; (2) if the training data set is selected to include plots that are richer in diagnostic species of particular classes? Material: Species composition records (relevés) from 4186 plots of Czech grasslands. Methods: Plots were classified into 11 phytosociological alliances (expert classification) and into 11 clusters derived from numerical cluster analysis. Some plots were used for training the classifiers, which were the multi-layer perceptrons (MLP; a type of artificial neural network). Other plots were used for testing the performance of these classifiers. Plots used for training were selected (1) randomly; (2) according to higher representation of diagnostic species of par

  • Czech name

    Řízená klasifikace rostlinných společenstev pomocí umělých neuronových sítí

  • Czech description

    Testování umělých neuronových sítí jako metody řízená klasifikace rostlinných společenstev

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    EF - Botany

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA206%2F02%2F0957" target="_blank" >GA206/02/0957: Formalized classification of the semi-natural grassland vegetation of the Czech Republic</a><br>

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2005

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of Vegetation Science

  • ISSN

    110-9233

  • e-ISSN

  • Volume of the periodical

    16

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    CZ - CZECH REPUBLIC

  • Number of pages

    8

  • Pages from-to

    407-414

  • UT code for WoS article

  • EID of the result in the Scopus database