Automated machine learning-aided prediction and interpretation of gaseous by-products from the hydrothermal liquefaction of biomass-Reference-Cited by-同舟云学术

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Automated machine learning-aided prediction and interpretation of gaseous by-products from the hydrothermal liquefaction of biomass

Published:2024-10 Issue: Volume:945 Page:173939
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Zhang Weijin,Ai Zejian,Chen Qingyue,Chen Jiefeng,Xu Donghai,Cao Jianbing,Kapusta Krzysztof,Peng Haoyi,Leng Lijian,Li Hailong

Funder

Fundamental Research Funds for Central Universities of the Central South University

Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Province

Publisher

Elsevier BV

Reference58 articles.

1. Prediction of hydrogen yield from supercritical gasification process of sewage sludge using machine learning and particle swarm hybrid strategy;Aslam Khan;Int. J. Hydrog. Energy,2024

2. Estimation of root zone soil moisture from ground and remotely sensed soil information with multisensor data fusion and automated machine learning;Babaeian;Remote Sens. Environ.,2021

3. Automated machine learning-based models for predicting and evaluating antibiotic removal in constructed wetlands;Bao;Bioresour. Technol.,2023

4. Effects of reaction conditions on products and elements distribution via hydrothermal liquefaction of duckweed for wastewater treatment;Chen;Bioresour. Technol.,2020

5. Hydrothermal liquefaction of Elaeis guineensis trunks: lessons learned from a case study in Guatemala;Cutz;Ind. Crop. Prod.,2023

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