Comparative artificial neural network models for predicting kinetic parameters of biomass pyrolysis from the biomass characteristics
Artificial Neural Network (ANN) was proposed to predict kinetic parameters of biomass pyrolysis using simple inputs like proximate or ultimate analysis results. The advantage of predicting via ANN is that it does not require thermogravimetric analysis, unlike the traditional methods. This approach r...
Saved in:
| Main Authors: | Kiattikhoon Phuakpunk, Benjapon Chalermsinsuwan, Suttichai Assabumrungrat |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
|
| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025027689 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Advances in kinetics modeling of biomass pyrolysis
by: LI Liang, et al.
Published: (2024-04-01) -
Numerical Simulation and Optimization of Industrial-Scale Fluidized Bed Reactor Coupling Biomass Catalytic Pyrolysis Kinetics
by: Ruobing Lin, et al.
Published: (2025-07-01) -
Comprehensive thermal properties, kinetic, and thermodynamic analyses of biomass wastes pyrolysis via TGA and Coats-Redfern methodologies
by: Ocident Bongomin, et al.
Published: (2024-10-01) -
Fuzzy Neural Network Applications in Biomass Gasification and Pyrolysis for Biofuel Production: A Review
by: Vladimir Bukhtoyarov, et al.
Published: (2024-12-01) -
Catalytic Pyrolysis of Waste Biomass
by: Grigore Pșenovschi, et al.
Published: (2024-02-01)