Simulation and optimization of co-pyrolysis biochar using data enhanced interpretable machine learning and particle swarm algorithm-Reference-Cited by-同舟云学术

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Simulation and optimization of co-pyrolysis biochar using data enhanced interpretable machine learning and particle swarm algorithm

Published:2024-03 Issue: Volume:182 Page:107111
ISSN:0961-9534
Container-title:Biomass and Bioenergy
language:en
Short-container-title:Biomass and Bioenergy

Author:

Chen Chao,Liang Rui,Wang Junxia,Ge Yadong,Tao Junyu,Yan Beibei,Chen Guanyi

Funder

Natural Science Foundation of Tianjin Municipality

National Natural Science Foundation of China

Ministry of Science and Technology of the People's Republic of China

Publisher

Elsevier BV

Reference43 articles.

1. Synthesis optimization and adsorption modeling of biochar for pollutant removal via machine learning;Zhang;Biochar,2023

2. Insight into the co-pyrolysis of different blended feedstocks to biochar for the adsorption of organic and inorganic pollutants: a review;Ahmed;J. Clean. Prod.,2020

3. Utilizing support vector regression modeling to predict pyro product yields from microwave-assisted catalytic co-pyrolysis of biomass and waste plastics;Potnuri;Energy Convers. Manag.,2023

4. Characteristics prediction of hydrothermal biochar using data enhanced interpretable machine learning;Chen;Bioresour. Technol.,2023

5. Physics-informed machine learning methods for biomass gasification modeling by considering monotonic relationships;Ren;Bioresour. Technol.,2023

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Improved Dujiangyan Irrigation System Optimization (IDISO): A Novel Metaheuristic Algorithm for Hydrochar Characteristics;Processes;2024-06-26

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