Machine learning-based stacked ensemble model for predicting and regulating oxygen-containing compounds in nitrogen-rich pyrolysis bio-oil DOI

Hui Wang,

Dongmei Bi,

Zhisen He

et al.

Renewable Energy, Journal Year: 2024, Volume and Issue: unknown, P. 122330 - 122330

Published: Dec. 1, 2024

Language: Английский

Predictive Modeling of Product Yields in Microwave-Assisted Co-Pyrolysis of Biomass and Plastic with Enhanced Interpretability Using Explainable AI Approaches DOI

Nilesh S Rajpurohit,

P. K. Kamani, Maheswata Lenka

et al.

Journal of Analytical and Applied Pyrolysis, Journal Year: 2025, Volume and Issue: unknown, P. 107021 - 107021

Published: Feb. 1, 2025

Language: Английский

Citations

1
Prediction and optimization of key factors for catalytic O3 degradation of antibiotics based on Catboost model coupled Bayesian optimisation algorithm DOI
Xiaoxia Wang,

Xinnan Zheng,

Zipeng Huang

et al.

Journal of Water Process Engineering, Journal Year: 2025, Volume and Issue: 72, P. 107481 - 107481

Published: March 15, 2025

Language: Английский

Citations

0
Optimization of an Industrial Circulating Water System Based on Process Simulation and Machine Learning DOI Open Access
Yingjie Liu, Rongbo Shao,

Qing Ye

et al.

Processes, Journal Year: 2025, Volume and Issue: 13(2), P. 332 - 332

Published: Jan. 24, 2025

As an important part of industrial production, the optimization circulating water systems is great significance for improving energy efficiency and reducing operating costs. However, traditional methods lack real-time dynamic adjustment capabilities often cannot fully cope with complex changeable environment demands. Advances in computer technology can enable people to use machine learning models process information data ultimately help simplify simulation optimization. In this paper, system a Fluid Catalytic Cracking (FCC) unit optimized evaluated based on learning, adopting 284 sets data. The cooler network modified from parallel structure series mode, effect clarified using ASPEN HYSYS software V12. Meanwhile, fan power cooling tower predicted by employing Gradient Boosting Regression (GBR) model, influence parallel-to-series transformation discussed. It shown that modeling results are coincidence Converting design arrangement significantly decrease consumption, reduction 11%. also reduced 8% after Considering changes both consumption power, saved total economic cost 8.65%, decreased gas emission 2142.06 kg/h. By building prediction system, sequencing monitoring equipment parameters realized, which saves costs improves safety.

Language: Английский

Citations

0
Evaluation of the Coprocessing Feasibility of Bio-oil Extraction Fractions with Waste Cooking Oil for 100% Bio-Based Fuel Production in a Pilot-scale Riser DOI
Yudi Zhao, Yang Xu, Yunming Fang

et al.

Renewable Energy, Journal Year: 2025, Volume and Issue: unknown, P. 123295 - 123295

Published: April 1, 2025

Language: Английский

Citations

0
An overview of advancements in biomass pyrolysis modeling: Applications, challenges, and future perspectives in rotary reactors DOI

Chaowei Ma,

Rongwu Zhu, Yulei Ma

et al.

Biomass and Bioenergy, Journal Year: 2024, Volume and Issue: 193, P. 107568 - 107568

Published: Dec. 24, 2024

Language: Английский

Citations

2
A review on the role of various machine learning algorithms in microwave-assisted pyrolysis of lignocellulosic biomass waste DOI
Iradat Hussain Mafat,

Dadi Venkata Surya,

Chinta Sankar Rao

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 371, P. 123277 - 123277

Published: Nov. 11, 2024

Language: Английский

Citations

1
Machine learning-based stacked ensemble model for predicting and regulating oxygen-containing compounds in nitrogen-rich pyrolysis bio-oil DOI

Hui Wang,

Dongmei Bi,

Zhisen He

et al.

Renewable Energy, Journal Year: 2024, Volume and Issue: unknown, P. 122330 - 122330

Published: Dec. 1, 2024

Language: Английский

Citations

0