Řízená klasifikace rostlinných společenstev pomocí umělých neuronových sítí

Kód výsledku v 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>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Supervised classification of plant communities with artificial neural networks

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

Supervised classification of plant communities with artificial neural networks

Popis výsledku anglicky

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

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

EF - Botanika

OECD FORD obor

—

Projekt

<a href="/cs/project/GA206%2F02%2F0957" target="_blank" >GA206/02/0957: Formalizovaná klasifikace polopřirozené travinné vegetace České republiky</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2005

Kód důvěrnosti údajů

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

Název periodika

Journal of Vegetation Science

ISSN

110-9233

e-ISSN

—

Svazek periodika

16

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

8

Strana od-do

407-414

Kód UT WoS článku

—

EID výsledku v databázi Scopus

—