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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:

Application of Statistical and Artificial Intelligence Techniques for Medium-Term Electrical Energy Forecasting: A Case Study for a Regional Hospital
Oğuzhan Timur, Kasım Zor, Özgür Çelık, et al.
Journal of Sustainable Development of Energy Water and Environment Systems (2019) Vol. 8, Iss. 3, pp. 520-536
Open Access | Times Cited: 18

Showing 18 citing articles:

Artificial intelligence as a sustainable tool in wastewater treatment using membrane bioreactors
Mohammadreza Kamali, Lise Appels, Xiaobin Yu, et al.
Chemical Engineering Journal (2020) Vol. 417, pp. 128070-128070
Closed Access | Times Cited: 101
Recent progress in sustainable energy-efficient technologies and environmental impacts on energy systems
Milan Vujanović, Qiuwang Wang, Mousa S. Mohsen, et al.
Applied Energy (2020) Vol. 283, pp. 116280-116280
Closed Access | Times Cited: 98
Advances in integration of energy, water and environment systems towards climate neutrality for sustainable development
Şiir Kılkış, Goran Krajačić, Neven Duić, et al.
Energy Conversion and Management (2020) Vol. 225, pp. 113410-113410
Closed Access | Times Cited: 89
Enhancement of membrane system performance using artificial intelligence technologies for sustainable water and wastewater treatment: A critical review
Nguyen Duc Viet, Duksoo Jang, Yeomin Yoon, et al.
Critical Reviews in Environmental Science and Technology (2021) Vol. 52, Iss. 20, pp. 3689-3719
Closed Access | Times Cited: 56
The Impact of Digital Transformation on Environmental Sustainability
Thanh Cong Truong
Advances in Multimedia (2022) Vol. 2022, pp. 1-12
Open Access | Times Cited: 40
An Insight of Deep Learning Based Demand Forecasting in Smart Grids
Javier M. Aguiar-Pérez, María A. Pérez-Juárez
Sensors (2023) Vol. 23, Iss. 3, pp. 1467-1467
Open Access | Times Cited: 27
Electricity Load Demand Prediction for Microgrid Energy Management System Using Hybrid Adaptive Barnacle‐Mating Optimizer with Artificial Neural Network Algorithm
G. Indira, M. Bhavani, R. Brinda, et al.
Energy Technology (2024) Vol. 12, Iss. 5
Closed Access | Times Cited: 12
A comprehensive benchmark of machine learning-based algorithms for medium-term electric vehicle charging demand prediction
Ömer Can Tolun, Kasım Zor, Önder Tutsoy
The Journal of Supercomputing (2025) Vol. 81, Iss. 3
Open Access | Times Cited: 1
A scoping review of deep neural networks for electric load forecasting
Nicolai Bo Vanting, Zheng Ma, Bo Nørregaard Jôrgensen
Energy Informatics (2021) Vol. 4, Iss. S2
Open Access | Times Cited: 46
Short-Term Building Electrical Energy Consumption Forecasting by Employing Gene Expression Programming and GMDH Networks
Kasım Zor, Özgür Çelık, Oğuzhan Timur, et al.
Energies (2020) Vol. 13, Iss. 5, pp. 1102-1102
Open Access | Times Cited: 29
Comparison of Artificial Intelligence and Machine LearningMethods used in Electric Power System Operation
Marcel Hallmann, Robert Pietracho, Przemlyslaw Komarnicki
(2024)
Open Access | Times Cited: 3
Developing of an Offline Monitoring Method for the Energy Demand of a Healthcare Facility in Italy
Marco Zini, Carlo Carcasci
Journal of Sustainable Development of Energy Water and Environment Systems (2022) Vol. 10, Iss. 4, pp. 1-22
Open Access | Times Cited: 10
Comparison of Artificial Intelligence and Machine Learning Methods Used in Electric Power System Operation
Marcel Hallmann, Robert Pietracho, Przemysław Komarnicki
Energies (2024) Vol. 17, Iss. 11, pp. 2790-2790
Open Access | Times Cited: 1
Machine learning para la predicción de energía eléctrica: una revisión sistemática de literatura
Kandel L. Yandar, Óscar Revelo Sánchez, Manuel Bolaños
Ingeniería y Competitividad (2024) Vol. 26, Iss. 2
Closed Access | Times Cited: 1
Exploring artificial intelligence methods for energy prediction in healthcare Facilities: An In-Depth extended systematic review
Marjan FatehiJananloo, Helen Stopps, J.J. McArthur
Energy and Buildings (2024) Vol. 320, pp. 114598-114598
Open Access | Times Cited: 1
Clustering and Deep-Learning for Energy Consumption Forecast in Smart Buildings
Desirée Arias-Requejo, Belarmino Pulido, Marcus Keane, et al.
IEEE Access (2023) Vol. 11, pp. 128061-128080
Open Access | Times Cited: 3
Systematic review of the use of artificial intelligence methods in hospital energy prediction
Marjan FatehiJananloo, Helen Stopps, J.J. McArthur
Building Simulation Conference proceedings (2023) Vol. 18
Open Access | Times Cited: 1
Impact of moisture buffering effect in the calibration of historical buildings energy models: a case study
Harold Enrique Huerto-Cardenas, Fabrizio Leonforte, Claudio Del Pero, et al.
Journal of Sustainable Development of Energy Water and Environment Systems (2020) Vol. N/A, Iss. N/A
Open Access | Times Cited: 1
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