Compensating for the loss of future tree values in the model of Fuzzy knowledge units
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F22%3A91207" target="_blank" >RIV/60460709:41110/22:91207 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1618866722001704" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1618866722001704</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ufug.2022.127627" target="_blank" >10.1016/j.ufug.2022.127627</a>
Alternative languages
Result language
angličtina
Original language name
Compensating for the loss of future tree values in the model of Fuzzy knowledge units
Original language description
In this paper, we describe a model for valuing solitary trees that allows the use of vague evaluation of input parameters for the evaluation of trees based on fuzzy knowledge units. The creation of the model is based on the parametric method of the Nature Conservation Agency (NCA) and other methods such as CAVAT or FEM, from which the knowledge text is separated. Fuzzy knowledge units (FKU) or Knowledge units (KU) are created from this knowledge text. These FKU are trained according to data from the NCA method and optimized using the MATLAB Tune fuzzy inference system (TUNEFIS). The Adaptive neuro fuzzy inference system (ANFIS) was chosen as the best FKU model. These fuzzy knowledge units are arranged in a hierarchical model of valuing solitary trees, which is implemented in Simulink. The experimental study clearly shows that the proposed model is more detailed in some parameters than a crisp tree evaluation calculator or CAVAT calculator and provides more precise results.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50704 - Environmental sciences (social aspects)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Urban Forestry & Urban Greening
ISSN
1618-8667
e-ISSN
1610-8167
Volume of the periodical
74
Issue of the periodical within the volume
August 2022
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
10
Pages from-to
1-10
UT code for WoS article
000812900600003
EID of the result in the Scopus database
2-s2.0-85132565846