Use of machine learning tools to estimate drying rate of apple and apricot wood discs

This study compares three machine learning (ML) models -artificial neural networks (ANN), recurrent neural networks (RNN), and extreme gradient boosting (XGBoost)- for predicting the drying kinetics of wood biomass from the clearing of outdated apple and apricot orchards. The primary goal was to op...

詳細記述

書誌詳細

主要な著者:	Martina Balac, Andrija Rajković, Mihailo Milanović, Zoran Mileusnić, Rajko Miodragović, Aleksandra Dragičević, Olivera Ećim-Đurić
フォーマット:	Artigo
言語:	Inglês
出版事項:	PAGEPress Publications 2025-09-01
シリーズ:	Journal of Agricultural Engineering
主題:	artificial neural network recurrent neural networks XGBoost wood drying
オンライン･アクセス:	https://www.agroengineering.org/jae/article/view/1712
タグ:	タグ追加 タグなし, このレコードへの初めてのタグを付けませんか!