Implementing the formal language of the vegetation classification expert systems (ESy) in the statistical computing environment R

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F21%3A00119069" target="_blank" >RIV/00216224:14310/21:00119069 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1111/avsc.12562" target="_blank" >https://doi.org/10.1111/avsc.12562</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/avsc.12562" target="_blank" >10.1111/avsc.12562</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Implementing the formal language of the vegetation classification expert systems (ESy) in the statistical computing environment R

Popis výsledku v původním jazyce

Aims The machine-readable formal language of classification expert systems has become a standard for applying plot assignment rules in vegetation classification. Here we present an efficient algorithm implementing the vegetation classification expert system in the statistical programming language R. Methods The principal idea of the R implementation is to solve the assignments to vegetation types not sequentially plot by plot but to parse the assignment rules into (nested) components that each can be evaluated by simultaneous vector-based processing of all plots in a database. Results and conclusions We demonstrate the algorithm taking the EUNIS classification expert system of European habitat types (EUNIS-ESy) as an example. The R code version of the vegetation classification expert system is particularly useful in large vegetation-plot databases because it solves all logical operations vector-wise across all plots, allowing for efficient evaluation of membership expressions and formulas. Another advantage of the R implementation is that membership formulas are not only readable but can also be produced as a machine-written result, for example as the output of classification algorithms run in R.

Název v anglickém jazyce

Implementing the formal language of the vegetation classification expert systems (ESy) in the statistical computing environment R

Popis výsledku anglicky

Aims The machine-readable formal language of classification expert systems has become a standard for applying plot assignment rules in vegetation classification. Here we present an efficient algorithm implementing the vegetation classification expert system in the statistical programming language R. Methods The principal idea of the R implementation is to solve the assignments to vegetation types not sequentially plot by plot but to parse the assignment rules into (nested) components that each can be evaluated by simultaneous vector-based processing of all plots in a database. Results and conclusions We demonstrate the algorithm taking the EUNIS classification expert system of European habitat types (EUNIS-ESy) as an example. The R code version of the vegetation classification expert system is particularly useful in large vegetation-plot databases because it solves all logical operations vector-wise across all plots, allowing for efficient evaluation of membership expressions and formulas. Another advantage of the R implementation is that membership formulas are not only readable but can also be produced as a machine-written result, for example as the output of classification algorithms run in R.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10611 - Plant sciences, botany

Projekt

<a href="/cs/project/GX19-28491X" target="_blank" >GX19-28491X: Centrum pro evropské vegetační syntézy (CEVS)</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Applied Vegetation Science

ISSN

1402-2001

e-ISSN

1654-109X

Svazek periodika

24

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

7

Strana od-do

„e12562“

Kód UT WoS článku

000636291500003

EID výsledku v databázi Scopus

2-s2.0-85103416653