Biomass Hydrothermal Gasification Characteristics Study: Based on Deep Learning for Data Generation and Screening Strategies DOI

Jingwei Qi,

Yijie Wang, Pengcheng Xu

et al.

Energy, Journal Year: 2024, Volume and Issue: unknown, P. 133492 - 133492

Published: Oct. 1, 2024

Language: Английский

Machine learning models for predicting biochar properties from lignocellulosic biomass torrefaction DOI
Guangcan Su, Peng Jiang

Bioresource Technology, Journal Year: 2024, Volume and Issue: 399, P. 130519 - 130519

Published: March 2, 2024

Language: Английский

Citations

13
Machine learning for sustainable organic waste treatment: a critical review DOI Creative Commons
Rohit Gupta,

Zahra Hajabdollahi Ouderji,

Uzma Uzma

et al.

npj Materials Sustainability, Journal Year: 2024, Volume and Issue: 2(1)

Published: April 8, 2024

Abstract Data-driven modeling is being increasingly applied in designing and optimizing organic waste management toward greater resource circularity. This study investigates a spectrum of data-driven techniques for treatment, encompassing neural networks, support vector machines, decision trees, random forests, Gaussian process regression, k -nearest neighbors. The application these explored terms their capacity complex processes. Additionally, the delves into physics-informed highlighting significance integrating domain knowledge improved model consistency. Comparative analyses are carried out to provide insights strengths weaknesses each technique, aiding practitioners selecting appropriate models diverse applications. Transfer learning specialized network variants also discussed, offering avenues enhancing predictive capabilities. work contributes valuable field modeling, emphasizing importance understanding nuances technique informed decision-making various treatment scenarios.

Language: Английский

Citations

11
Thermogravimetric experiments based prediction of biomass pyrolysis behavior: A comparison of typical machine learning regression models in Scikit-learn DOI
Zhong Yu,

Fahang Liu,

Guozhe Huang

et al.

Marine Pollution Bulletin, Journal Year: 2024, Volume and Issue: 202, P. 116361 - 116361

Published: April 17, 2024

Language: Английский

Citations

11
Pyrolysis parameter based optimization study using response surface methodology and machine learning for potato stalk DOI
Ahmad Nawaz, Shaikh A. Razzak, Pradeep Kumar

et al.

Journal of the Taiwan Institute of Chemical Engineers, Journal Year: 2024, Volume and Issue: 159, P. 105476 - 105476

Published: April 6, 2024

Language: Английский

Citations

8
Pyrolysis preparation of battery-grade Li2CO3 using the Higee-microwave coupled reactor: Process optimization and AI modeling DOI
Yue Liu,

Xiaokang Pei,

Cong Chen

et al.

Chemical Engineering and Processing - Process Intensification, Journal Year: 2025, Volume and Issue: unknown, P. 110159 - 110159

Published: Jan. 1, 2025

Language: Английский

Citations

1
A novel hydrochar production from corn stover and sewage sludge: Synergistic co-hydrothermal carbonization understandings through deep machine learning and modelling DOI
Tiankai Zhang, Qiliang Wang

Renewable Energy, Journal Year: 2025, Volume and Issue: unknown, P. 122628 - 122628

Published: Feb. 1, 2025

Language: Английский

Citations

1
Effects of alkali and alkaline earth metals in biomass on co-pyrolysis characteristics and product distribution of coal and biomass DOI
Na Liu, He Huang,

Jun Feng

et al.

Fuel, Journal Year: 2025, Volume and Issue: 389, P. 134551 - 134551

Published: Feb. 7, 2025

Language: Английский

Citations

1
Modeling and kinetic analysis for co-pyrolysis of sewage sludge and municipal solid waste under multiple factors DOI
Hongnan Zhang,

Yunan Sun,

Junyu Tao

et al.

Environment Development and Sustainability, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 7, 2025

Language: Английский

Citations

1
Study on the Co-gasification characteristics of biomass and municipal solid waste based on machine learning DOI

Jingwei Qi,

Yijie Wang, Pengcheng Xu

et al.

Energy, Journal Year: 2023, Volume and Issue: 290, P. 130178 - 130178

Published: Dec. 29, 2023

Language: Английский

Citations

20
Multi-output neural network model for predicting biochar yield and composition DOI
Yifan Wang,

Liang Xu,

Jianen Li

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 945, P. 173942 - 173942

Published: June 15, 2024

Language: Английский

Citations

6