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:

Predicting the PCM-incorporated building's performance using optimized linear kernel and tree-based machine learning methods
Kashif Nazir, Shazim Ali Memon, Assemgul Saurbayeva
Journal of Energy Storage (2024) Vol. 94, pp. 112495-112495
Closed Access | Times Cited: 8

Showing 8 citing articles:

Sustainable Development Goals and Energy Efficiency in Educational Institutions Through Smart Buildings and Machine Learning
Eda Tabaku, Eli Vyshka, Rinela Kapçiu
Journal of Lifestyle and SDGs Review (2025) Vol. 5, Iss. 3, pp. e05010-e05010
Closed Access

A review of artificial intelligence to thermal energy storage and heat transfer improvement in phase change materials
Artur Nemś, Sindu Daniarta, Magdalena Nemś, et al.
Sustainable materials and technologies (2025), pp. e01348-e01348
Closed Access

A machine learning and deep learning approach to the identification of heat transfer and phase change phenomena in cement mortar walls filled with bio-based PCM
Mohammed-Hichem Benzaama, Abderrahim Boudenne, Karim Benzarti
Journal of Energy Storage (2025) Vol. 121, pp. 116540-116540
Closed Access

Phase Change Materials in Residential Buildings: Challenges, Opportunities, and Performance
José Pereira, Reinaldo Rodrigues de Souza, Jéferson Diehl de Oliveira, et al.
Materials (2025) Vol. 18, Iss. 9, pp. 2063-2063
Open Access

Comparative analysis of shallow and deep machine learning models for predicting indoor thermal response of flexible envelope system
Lifei Ye, Yunfei Ding
Journal of Energy Storage (2025) Vol. 126, pp. 116997-116997
Closed Access

A novel framework for developing a machine learning-based forecasting model using multi-stage sensitivity analysis to predict the energy consumption of PCM-integrated building
Kashif Nazir, Shazim Ali Memon, Assemgul Saurbayeva
Applied Energy (2024) Vol. 376, pp. 124180-124180
Closed Access | Times Cited: 2

Energy consumption forecasting in PCM-integration buildings considering building and environmental parameters for future climate scenarios.
Xeniya Aliyeva, Shazim Ali Memon, Kashif Nazir, et al.
Energy (2024), pp. 133248-133248
Closed Access | Times Cited: 1

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