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Trees classification based on Fourier coefficients of the sapflow density flux.

Authors :
Efrosinin, Dmitry
Kochetkova, Irina
Stepanova, Natalia
Yarovslavtsev, Alexey
Samouylov, Konstantin
Valentini, Riccardo
Source :
Annales Mathematicae et Informaticae. 2021, Vol. 53, p109-123. 15p.
Publication Year :
2021

Abstract

In this paper we study the possibility to use the artificial neural networks for trees classification based on real and approximated values of the sap flow density flux describing water transport in trees. The data sets were generated by means of a new tree monitoring system TreeTalker©. The Fourier series-based model is used for fitting the data sets with periodic patterns. The multivariate regression model defines the functional dependencies between sap flow density and temperature time series. The paper shows that Fourier coefficients can be successfully used as elements of the feature vectors required to solve different classification problems. Here we train multilayer neural networks to classify the trees according to different types of classes. The quality of the developed model for prediction and classification is verified by numerous numerical examples. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17875021
Volume :
53
Database :
Academic Search Index
Journal :
Annales Mathematicae et Informaticae
Publication Type :
Academic Journal
Accession number :
154303144
Full Text :
https://doi.org/10.33039/ami.2021.03.002