Artificial neural network model for the prediction of kinetic parameters of biomass pyrolysis from its constituents

By Sasithorn Sunphorka, B. Chalermsinsuwan, P. Piumsomboon. 2017

181 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Materials Chemistry

View Paper: https://www.semanticscholar.org/paper/372073c222b1d2e57c68c764d7d16db8159adfc5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. C. Tsekos
2. W. de Jong
3. S. Tandurella

In Materials Chemistry

1. C. Tsekos
2. W. de Jong
3. S. Tandurella

Citations in the corpus

• Estimation of lignocellulosic biomass pyrolysis product yields using artificial neural networks (2021, methodology): “In general, the inherent ability of ANN models to process large amounts of data has led to the development of quite a few models that employ data available from multiple literature sources for pyrolysis [6, 21,22,25], combustion [29] and gasification [28,30,31].”