Predicted versus observed antler beam diameter and length for test dataset by Linear model and Levenberg–Marquardt (L-M), Bayesian Regularization (BR) and Scaled Conjugate Gradient (SCG) learning algorithms in the Artificial Neural Network (ANN) model.</p
Aim of Study: As an innovative prediction technique, Artificial Intelligence technique based on a De...
The financial exploitation of forests constitutes an important part of human activity. This effort i...
Abstract Taper functions and volume equations are essential for estimation of the individual volume,...
Pearson correlation coefficients between observed and predicted antler beam diameter and length base...
Mean squared error based on the number of neurons using Levenberg–Marquardt (L-M), Bayesian Regulari...
Evaluation of harvest data remains one of the most important sources of information in the developme...
Evaluation of harvest data remains one of the most important sources of information in the developme...
Effect of the number of neurons on the performance of Levenberg–Marquardt (L-M), Bayesian Regulariza...
Metrics for model performance using antler beam diameter and length from test dataset.</p
The objective of this study is to compare the predictive ability of Bayesian regularization with Lev...
The objective of this study is to compare the predictive ability of Bayesian regularization with Lev...
<p>Residuals of diameter predictions (cm) versus tree stem diameters (cm) in the upper plots, as wel...
Accuracy measurements of the artificial neural network model (ANN), the polynomial regression equati...
Accuracy measurements of the artificial neural network model (ANN), the polynomial regression equati...
Values on axes refer to normalized species richness. The determination coefficient for the ANN model...
Aim of Study: As an innovative prediction technique, Artificial Intelligence technique based on a De...
The financial exploitation of forests constitutes an important part of human activity. This effort i...
Abstract Taper functions and volume equations are essential for estimation of the individual volume,...
Pearson correlation coefficients between observed and predicted antler beam diameter and length base...
Mean squared error based on the number of neurons using Levenberg–Marquardt (L-M), Bayesian Regulari...
Evaluation of harvest data remains one of the most important sources of information in the developme...
Evaluation of harvest data remains one of the most important sources of information in the developme...
Effect of the number of neurons on the performance of Levenberg–Marquardt (L-M), Bayesian Regulariza...
Metrics for model performance using antler beam diameter and length from test dataset.</p
The objective of this study is to compare the predictive ability of Bayesian regularization with Lev...
The objective of this study is to compare the predictive ability of Bayesian regularization with Lev...
<p>Residuals of diameter predictions (cm) versus tree stem diameters (cm) in the upper plots, as wel...
Accuracy measurements of the artificial neural network model (ANN), the polynomial regression equati...
Accuracy measurements of the artificial neural network model (ANN), the polynomial regression equati...
Values on axes refer to normalized species richness. The determination coefficient for the ANN model...
Aim of Study: As an innovative prediction technique, Artificial Intelligence technique based on a De...
The financial exploitation of forests constitutes an important part of human activity. This effort i...
Abstract Taper functions and volume equations are essential for estimation of the individual volume,...