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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:

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

Showing 26-50 of 152 citing articles:

Prediction of HHV of fuel by Machine learning Algorithm: Interpretability analysis using Shapley Additive Explanations (SHAP)
Manish Sharma Timilsina, Subhadip Sen, Bibek Uprety, et al.
Fuel (2023) Vol. 357, pp. 129573-129573
Closed Access | Times Cited: 33
Machine learning models for predicting biochar properties from lignocellulosic biomass torrefaction
Guangcan Su, Peng Jiang
Bioresource Technology (2024) Vol. 399, pp. 130519-130519
Closed Access | Times Cited: 13
Estimation of pore structure and permeability in tight carbonate reservoir based on machine learning (ML) algorithm using SEM images of Jaisalmer sub-basin, India
Pydiraju Yalamanchi, Saurabh Datta Gupta
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 12
Thermogravimetric experiments based prediction of biomass pyrolysis behavior: A comparison of typical machine learning regression models in Scikit-learn
Zhong Yu, Fahang Liu, Guozhe Huang, et al.
Marine Pollution Bulletin (2024) Vol. 202, pp. 116361-116361
Closed Access | Times Cited: 11
Machine learning for sustainable organic waste treatment: a critical review
Rohit Gupta, Zahra Hajabdollahi Ouderji, Uzma Uzma, et al.
npj Materials Sustainability (2024) Vol. 2, Iss. 1
Open Access | Times Cited: 10
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
Machine learning (ML): An emerging tool to access the production and application of biochar in the treatment of contaminated water and wastewater
Sheetal Kumari, Jyoti Chowdhry, Manish Kumar, et al.
Groundwater for Sustainable Development (2024) Vol. 26, pp. 101243-101243
Closed Access | Times Cited: 8
Robust intelligent topology for estimation of heat capacity of biochar pyrolysis residues
Mohsen Karimi, Elnaz Aminzadehsarikhanbeglou, Behzad Vaferi
Measurement (2021) Vol. 183, pp. 109857-109857
Closed Access | Times Cited: 50
Intelligent modeling for considering the effect of bio-source type and appearance shape on the biomass heat capacity
Mohsen Karimi, Ali Hosin Alibak, Seyed Mehdi Alizadeh, et al.
Measurement (2021) Vol. 189, pp. 110529-110529
Closed Access | Times Cited: 48
Progress in thermodynamic simulation and system optimization of pyrolysis and gasification of biomass
Yang Zhang, Yuanhui Ji, Hongliang Qian
Green Chemical Engineering (2021) Vol. 2, Iss. 3, pp. 266-283
Open Access | Times Cited: 45
Prediction of torrefied biomass properties from raw biomass
Furkan Kartal, Uğur Özveren
Renewable Energy (2021) Vol. 182, pp. 578-591
Closed Access | Times Cited: 42
Determination of the heat capacity of cellulosic biosamples employing diverse machine learning approaches
Mohsen Karimi, Marzieh Khosravi, Reza Fathollahi, et al.
Energy Science & Engineering (2022) Vol. 10, Iss. 6, pp. 1925-1939
Open Access | Times Cited: 34
Machine learning models for biomass energy content prediction: A correlation-based optimal feature selection approach
Usman Alhaji Dodo, Evans Chinemezu Ashigwuike, Sani I. Abba
Bioresource Technology Reports (2022) Vol. 19, pp. 101167-101167
Closed Access | Times Cited: 34
Thermal degradation characteristics, kinetic and thermodynamic analyses of date palm surface fibers at different heating rates
Abrar Inayat, Farrukh Jamil, Shams Forruque Ahmed, et al.
Fuel (2022) Vol. 335, pp. 127076-127076
Closed Access | Times Cited: 30
Artificial Intelligence and Mathematical Models of Power Grids Driven by Renewable Energy Sources: A Survey
Sabarathinam Srinivasan, Suresh Kumarasamy, Zacharias Andreadakis, et al.
Energies (2023) Vol. 16, Iss. 14, pp. 5383-5383
Open Access | Times Cited: 18
Estimation of the main air pollutants from different biomasses under combustion atmospheres by artificial neural networks
Thalyssa Oliveira Monteiro, Pedro Augusto Araújo da Silva de Almeida Nava Alves, Alex Oliveira Barradas Filho, et al.
Chemosphere (2024) Vol. 352, pp. 141484-141484
Closed Access | Times Cited: 7
Exploring Insights in Biomass and Waste Gasification via Ensemble Machine Learning Models and Interpretability Techniques
Ocident Bongomin, Charles Nzila, Josphat Igadwa Mwasiagi, et al.
International Journal of Energy Research (2024) Vol. 2024, Iss. 1
Open Access | Times Cited: 7
Prediction of the higher heating values of biomass using machine learning methods based on proximate and ultimate analysis
Abdülkadir Koçer
Journal of Mechanical Science and Technology (2024) Vol. 38, Iss. 3, pp. 1569-1574
Closed Access | Times Cited: 6
Pelletizing of lignocellulosic wastes as an environmentally friendly solution for the energy supply: insights on the properties of pellets from Brazilian biomasses
Diego Abner Rodrigues Santana, Mário Vanoli Scatolino, Michael Douglas Roque Lima, et al.
Environmental Science and Pollution Research (2020) Vol. 28, Iss. 9, pp. 11598-11617
Closed Access | Times Cited: 45
Classification of solid fuels with machine learning
Furkan Elmaz, Barkın Büyükçakır, Özgün Yücel, et al.
Fuel (2020) Vol. 266, pp. 117066-117066
Closed Access | Times Cited: 44
Combustion of Biomass in Fluidized Beds: A Review of Key Phenomena and Future Perspectives
K.Y. Kwong, Ewa Marek
Energy & Fuels (2021) Vol. 35, Iss. 20, pp. 16303-16334
Open Access | Times Cited: 37
Bagging based ensemble learning approaches for modeling the emission of PCDD/Fs from municipal solid waste incinerators
Ken Chen, Yaqi Peng, Shengyong Lu, et al.
Chemosphere (2021) Vol. 274, pp. 129802-129802
Closed Access | Times Cited: 36
The Estimation of the Higher Heating Value of Biochar by Data-Driven Modeling
Jiefeng Chen, Linxian Ding, Pengyu Wang, et al.
JOURNAL OF RENEWABLE MATERIALS (2022) Vol. 10, Iss. 6, pp. 1555-1574
Open Access | Times Cited: 24
Spatio-temporal prediction of temperature in fluidized bed biomass gasifier using dynamic recurrent neural network method
Ibtihaj Khurram Faridi, Evangelos Tsotsas, Wolfram Heineken, et al.
Applied Thermal Engineering (2022) Vol. 219, pp. 119334-119334
Closed Access | Times Cited: 22
Effects of biomass particles size and shape on combustion process in the swirl-stabilized burner reactor: CFD and machine learning approach
Aleksandar Milićević, Srdjan Belošević, Mileta Žarković, et al.
Biomass and Bioenergy (2023) Vol. 174, pp. 106817-106817
Closed Access | Times Cited: 15

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