Energy simulation and variable analysis of refining process in thermo-mechanical pulp mill using machine learning approach

DOI10.1080/13873954.2021.1990967zbMath1485.93420OpenAlexW3211015018MaRDI QIDQ5070704

No author found.

Publication date: 14 April 2022

Published in: Mathematical and Computer Modelling of Dynamical Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/13873954.2021.1990967

zbMATH Keywords

artificial intelligencedata analysismultilayer perceptronrefining energy simulationrefining parametric studythermo-mechanical pulping

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Application models in control theory (93C95)

Uses Software

• PRMLT

Cites Work

• Unnamed Item
• Unnamed Item
• Self-tuning control of a chip refiner motor load
• Application of an Artificial Neural Network for Modelling the Thermal Dynamics of a Building?s Space and its Heating System
• First principles versus artificial neural network modelling of a solar desalination system with experimental validation
• Use of modelling and simulation in the pulp and paper industry
• Application of advanced data treatment to predict paper properties

This page was built for publication: Energy simulation and variable analysis of refining process in thermo-mechanical pulp mill using machine learning approach