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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Estimating biomass major chemical constituents from ultimate analysis using a random forest model
Jiangkuan Xing, Kun Luo, Haiou Wang, et al.
Bioresource Technology (2019) Vol. 288, pp. 121541-121541
Closed Access | Times Cited: 71

Showing 1-25 of 71 citing articles:

Recent advances of thermochemical conversion processes for biorefinery
Myung Won Seo, See Hoon Lee, Hyungseok Nam, et al.
Bioresource Technology (2021) Vol. 343, pp. 126109-126109
Closed Access | Times Cited: 198
A comprehensive study on estimating higher heating value of biomass from proximate and ultimate analysis with machine learning approaches
Jiangkuan Xing, Kun Luo, Haiou Wang, et al.
Energy (2019) Vol. 188, pp. 116077-116077
Closed Access | Times Cited: 152
The role of machine learning to boost the bioenergy and biofuels conversion
Zheng‐Xin Wang, Xinggan Peng, Ao Xia, et al.
Bioresource Technology (2021) Vol. 343, pp. 126099-126099
Closed Access | Times Cited: 125
A comparative study of machine learning methods for bio-oil yield prediction – A genetic algorithm-based features selection
Zahid Ullah, Muzammil Khan, Salman Raza Naqvi, et al.
Bioresource Technology (2021) Vol. 335, pp. 125292-125292
Closed Access | Times Cited: 121
Interpretable machine learning for predicting and evaluating hydrogen production via supercritical water gasification of biomass
Sheng Zhao, Jian Li, Chao Chen, et al.
Journal of Cleaner Production (2021) Vol. 316, pp. 128244-128244
Closed Access | Times Cited: 114
Machine learning modeling and analysis of biohydrogen production from wastewater by dark fermentation process
Ahmad Hosseinzadeh, John L. Zhou, Ali Altaee, et al.
Bioresource Technology (2021) Vol. 343, pp. 126111-126111
Open Access | Times Cited: 111
Applications of artificial intelligence‐based modeling for bioenergy systems: A review
Mochen Liao, Yuan Yao
GCB Bioenergy (2021) Vol. 13, Iss. 5, pp. 774-802
Open Access | Times Cited: 103
Machine-learning-aided thermochemical treatment of biomass: a review
Hailong Li, Jiefeng Chen, Weijin Zhang, et al.
Biofuel Research Journal (2023) Vol. 10, Iss. 1, pp. 1786-1809
Open Access | Times Cited: 96
Characteristics prediction of hydrothermal biochar using data enhanced interpretable machine learning
Chao Chen, Zhi Wang, Yadong Ge, et al.
Bioresource Technology (2023) Vol. 377, pp. 128893-128893
Closed Access | Times Cited: 41
Enhancing biomass Pyrolysis: Predictive insights from process simulation integrated with interpretable Machine learning models
Douglas Chinenye Divine, Stell Hubert, Emmanuel I. Epelle, et al.
Fuel (2024) Vol. 366, pp. 131346-131346
Closed Access | Times Cited: 22
A review on the overall process of lignin to phenolic compounds for chemicals and fuels: From separation and extraction of lignin to transformation
Yao Tong, Tianhua Yang, Jian Wang, et al.
Journal of Analytical and Applied Pyrolysis (2024) Vol. 181, pp. 106663-106663
Closed Access | Times Cited: 17
Prediction of Bio-oil Yield and Hydrogen Contents Based on Machine Learning Method: Effect of Biomass Compositions and Pyrolysis Conditions
Qinghui Tang, Yingquan Chen, Haiping Yang, et al.
Energy & Fuels (2020) Vol. 34, Iss. 9, pp. 11050-11060
Closed Access | Times Cited: 124
Insights into the bioenergy potential of jackfruit wastes considering their physicochemical properties, bioenergy indicators, combustion behaviors, and emission characteristics
José Luiz Francisco Alves, Jean Constantino Gomes da Silva, Guilherme Davi Mumbach, et al.
Renewable Energy (2020) Vol. 155, pp. 1328-1338
Closed Access | Times Cited: 81
Machine learning prediction of bio-oil characteristics quantitatively relating to biomass compositions and pyrolysis conditions
Tonghuan Zhang, Danyang Cao, Xin Feng, et al.
Fuel (2021) Vol. 312, pp. 122812-122812
Closed Access | Times Cited: 78
Predicting co-pyrolysis of coal and biomass using machine learning approaches
Hao Wei, Kun Luo, Jiangkuan Xing, et al.
Fuel (2021) Vol. 310, pp. 122248-122248
Closed Access | Times Cited: 71
Prediction and optimization of syngas production from steam gasification: Numerical study of operating conditions and biomass composition
Jishuo Li, Kaili Xu, Xiwen Yao, et al.
Energy Conversion and Management (2021) Vol. 236, pp. 114077-114077
Closed Access | Times Cited: 69
Machine learning prediction of lignin content in poplar with Raman spectroscopy
Wenli Gao, Liang Zhou, Shengquan Liu, et al.
Bioresource Technology (2022) Vol. 348, pp. 126812-126812
Closed Access | Times Cited: 55
Machine learning technology in biohydrogen production from agriculture waste: Recent advances and future perspectives
Amit Kumar Sharma, Praveen Kumar Ghodke, Nishu Goyal, et al.
Bioresource Technology (2022) Vol. 364, pp. 128076-128076
Closed Access | Times Cited: 53
Prediction of uranium adsorption capacity on biochar by machine learning methods
Tianxing Da, Hui-Kang Ren, Wen-ke He, et al.
Journal of environmental chemical engineering (2022) Vol. 10, Iss. 5, pp. 108449-108449
Closed Access | Times Cited: 51
State-of-the-art and future directions of machine learning for biomass characterization and for sustainable biorefinery
Aditya Velidandi, Pradeep Kumar Gandam, Madhavi Latha Chinta, et al.
Journal of Energy Chemistry (2023) Vol. 81, pp. 42-63
Closed Access | Times Cited: 37
Characterization of natural cellulosic fiber extracted from Grewia ferruginea plant stem
Bantamlak Birlie, Tekalgn Mamay
International Journal of Biological Macromolecules (2024) Vol. 271, pp. 132858-132858
Closed Access | Times Cited: 11
Machine learning prediction of bio-oil production from the pyrolysis of lignocellulosic biomass: Recent advances and future perspectives
Hyojin Lee, Il-Ho Choi, Kyung-Ran Hwang
Journal of Analytical and Applied Pyrolysis (2024) Vol. 179, pp. 106486-106486
Open Access | Times Cited: 9
Waste-to-energy in the civil-construction sector toward the valuation of wood construction residues: Integration of torrefaction process
Thais Barbosa, Bruno S. Chaves, Luiz Gustavo Oliveira Galvão, et al.
Fuel (2024) Vol. 371, pp. 132029-132029
Closed Access | Times Cited: 9
A deep learning approach for prediction of syngas lower heating value from CFB gasifier in Aspen plus®
Furkan Kartal, Uğur Özveren
Energy (2020) Vol. 209, pp. 118457-118457
Closed Access | Times Cited: 65
A hybridized model based on neural network and swarm intelligence-grey wolf algorithm for spatial prediction of urban flood-inundation
Hamid Darabi, Ali Torabi Haghighi, Omid Rahmati, et al.
Journal of Hydrology (2021) Vol. 603, pp. 126854-126854
Open Access | Times Cited: 52
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