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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.

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Showing 1-25 of 36 citing articles:

Palladium Price Predictions via Machine Learning
Bingzi Jin, Xiaojie Xu
Materials Circular Economy (2024) Vol. 6, Iss. 1
Closed Access | Times Cited: 40
Thermal coal futures trading volume predictions through the neural network
Bingzi Jin, Xiaojie Xu, Yun Zhang
Journal of Modelling in Management (2024)
Closed Access | Times Cited: 22
A comparative assessment of machine learning methods for predicting housing prices using Bayesian optimization
Salim Lahmiri, Stelios Bekiros, Christos Avdoulas
Decision Analytics Journal (2023) Vol. 6, pp. 100166-100166
Open Access | Times Cited: 31
Cryptocurrencies Are Becoming Part of the World Global Financial Market
Marcin Wątorek, Jarosław Kwapień, Stanisław Drożdż
Entropy (2023) Vol. 25, Iss. 2, pp. 377-377
Open Access | Times Cited: 26
Optimal hybrid artificial intelligence models for predicting the adsorptive removal of dyes and phenols from aqueous solutions using an amine-functionalized graphene oxide/layered triple hydroxide nanocomposite
Hamdi A. Al-Jamimi, Salem A. Bahadi, Galal M. BinMakhashen, et al.
Journal of Molecular Liquids (2023) Vol. 391, pp. 123374-123374
Closed Access | Times Cited: 19
Connectedness of cryptocurrency markets to crude oil and gold: an analysis of the effect of COVID-19 pandemic
Parisa Foroutan, Salim Lahmiri
Financial Innovation (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 6
Deep learning systems for forecasting the prices of crude oil and precious metals
Parisa Foroutan, Salim Lahmiri
Financial Innovation (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 5
Machine learning platinum price predictions
Bingzi Jin, Xiaojie Xu
The Engineering Economist (2025), pp. 1-27
Closed Access
Forecasting International Electricity Market Prices by Using Optimized Machine Learning Systems
Salim Lahmiri
Smart Grids and Sustainable Energy (2025) Vol. 10, Iss. 1
Closed Access
Scrap steel price predictions for southwest China via machine learning
Bingzi Jin, Xiaojie Xu
Innovation and Emerging Technologies (2025) Vol. 12
Closed Access
Wavelet Entropy for Efficiency Assessment of Price, Return, and Volatility of Brent and WTI During Extreme Events
Salim Lahmiri
Commodities (2025) Vol. 4, Iss. 2, pp. 4-4
Open Access
Study on waste tire pyrolysis product characteristics based on machine learning
Jingwei Qi, Kaihong Zhang, Ming Hu, et al.
Journal of environmental chemical engineering (2023) Vol. 11, Iss. 6, pp. 111314-111314
Closed Access | Times Cited: 13
Forecasting and trading credit default swap indices using a deep learning model integrating Merton and LSTMs
Weifang Mao, Huiming Zhu, Hao Wu, et al.
Expert Systems with Applications (2022) Vol. 213, pp. 119012-119012
Closed Access | Times Cited: 17
Fossil energy market price prediction by using machine learning with optimal hyper-parameters: A comparative study
Salim Lahmiri
Resources Policy (2024) Vol. 92, pp. 105008-105008
Closed Access | Times Cited: 3
Price disorder and information content in energy and gold markets: The effect of the COVID-19 pandemic
Salim Lahmiri
Energy Nexus (2024) Vol. 16, pp. 100343-100343
Closed Access | Times Cited: 3
Machine learning Brent crude oil price forecasts
Bingzi Jin, Xiaojie Xu
Innovation and Emerging Technologies (2024) Vol. 11
Closed Access | Times Cited: 3
Prediction of NH3 and HCN yield from biomass fast pyrolysis: Machine learning modeling and evaluation
Junyu Tao, Xiaoxiao Yin, Xilei Yao, et al.
The Science of The Total Environment (2023) Vol. 885, pp. 163743-163743
Closed Access | Times Cited: 8
A hybrid Bayesian optimization-based deep learning model for modeling the condition of saltwater pipes in Hong Kong
Eslam Mohammed Abdelkader, Tarek Zayed, Nehal Elshaboury, et al.
International Journal of Construction Management (2024), pp. 1-17
Closed Access | Times Cited: 2
Cryptocurrency trading: A systematic mapping study
Duy Thien An Nguyen, Ka Ching Chan
International Journal of Information Management Data Insights (2024) Vol. 4, Iss. 2, pp. 100240-100240
Closed Access | Times Cited: 2
Support vector regression-based heteroscedastic models for cryptocurrency risk forecasting
Intan Muchtadi-Alamsyah, Robin Viltoriano, Ferdinand Harjono, et al.
Applied Soft Computing (2024) Vol. 162, pp. 111792-111792
Closed Access | Times Cited: 2
Prediction of various parameters of desalination system using BOA- GPR machine learning technique for sustainable development: A case study
Neel Shrimali, V K Patel, Hitesh Panchal, et al.
Environmental Challenges (2023) Vol. 12, pp. 100729-100729
Open Access | Times Cited: 5
Bitcoin price prediction using LSTM, GRU and hybrid LSTM-GRU with bayesian optimization, random search, and grid search for the next days
I.sibel KERVANCI, Mehmet Fatih Akay, Eren Özceylan
Journal of Industrial and Management Optimization (2023) Vol. 20, Iss. 2, pp. 570-588
Open Access | Times Cited: 5
Bayesian machine learning framework for characterizing structural dependency, dynamics, and volatility of cryptocurrency market using potential field theory
C V Anoop, Neeraj Negi, Anup Aprem
Expert Systems with Applications (2024), pp. 125475-125475
Closed Access | Times Cited: 1
A comparative study of statistical machine learning methods for condition monitoring of electric drive trains in supply chains
Salim Lahmiri
Supply Chain Analytics (2023) Vol. 2, pp. 100011-100011
Open Access | Times Cited: 3
Behavioural antecedents of Bitcoin trading volume
Blanka Škrabić Perić, Petar Sorić, Ivana Jerković
Croatian Operational Research Review (2023) Vol. 14, Iss. 1, pp. 87-97
Open Access | Times Cited: 3
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