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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:

Daily electrical energy consumption: Periodicity, harmonic regression method and forecasting
Yılmaz Akdi, Elif Gölveren, Yasin Okkaoğlu
Energy (2019) Vol. 191, pp. 116524-116524
Closed Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

Prediction of transportation energy demand: Multivariate Adaptive Regression Splines
Mohammad Ali Sahraei, Hakan Duman, Muhammed Yasin Çodur, et al.
Energy (2021) Vol. 224, pp. 120090-120090
Closed Access | Times Cited: 53
A Comparative Study of Forecasting Electricity Consumption Using Machine Learning Models
Madeline Pe, Yee Ser, Ganeshsree Selvachandran, et al.
Mathematics (2022) Vol. 10, Iss. 8, pp. 1329-1329
Open Access | Times Cited: 37
A deep learning approach to model daily particular matter of Ankara: key features and forecasting
Yıldırım Akbal, Kamil Demirberk Ünlü
International Journal of Environmental Science and Technology (2021) Vol. 19, Iss. 7, pp. 5911-5927
Closed Access | Times Cited: 33
A univariate time series methodology based on sequence-to-sequence learning for short to midterm wind power production
Yıldırım Akbal, Kamil Demirberk Ünlü
Renewable Energy (2022) Vol. 200, pp. 832-844
Closed Access | Times Cited: 23
A hybrid time series forecasting approach integrating fuzzy clustering and machine learning for enhanced power consumption prediction
Khalaf Alsalem
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Identifying critical building-oriented features in city-block-level building energy consumption: A data-driven machine learning approach
Zhongnan Ye, Kuang-Ly Cheng, Shu‐Chien Hsu, et al.
Applied Energy (2021) Vol. 301, pp. 117453-117453
Open Access | Times Cited: 32
The new hybrid approaches to forecasting short-term electricity load
Guo‐Feng Fan, Yanrong Liu, Wei Hui-zhen, et al.
Electric Power Systems Research (2022) Vol. 213, pp. 108759-108759
Closed Access | Times Cited: 19
A hybrid MCDM method for enhancing site selection for wind power plants in Turkey
Zeynep Çolak
Energy Sustainable Development/Energy for sustainable development (2024) Vol. 82, pp. 101536-101536
Closed Access | Times Cited: 4
Long short-term memory (LSTM) neural network and adaptive neuro-fuzzy inference system (ANFIS) approach in modeling renewable electricity generation forecasting
Mehmet Bilgili, Alper Yıldırım, Arif Özbek, et al.
International Journal of Green Energy (2020) Vol. 18, Iss. 6, pp. 578-594
Closed Access | Times Cited: 30
A Data-Driven Model to Forecast Multi-Step Ahead Time Series of Turkish Daily Electricity Load
Kamil Demirberk Ünlü
Electronics (2022) Vol. 11, Iss. 10, pp. 1524-1524
Open Access | Times Cited: 18
An adaptive ensemble predictive strategy for multiple scale electrical energy usages forecasting
Jing Tian, Kangji Li, Wenping Xue
Sustainable Cities and Society (2020) Vol. 66, pp. 102654-102654
Closed Access | Times Cited: 27
Strategic Electricity Production Planning of Turkey via Mixed Integer Programming Based on Time Series Forecasting
Gökay Yörük, Uğur Baç, Fatma Yerlikaya–Özkurt, et al.
Mathematics (2023) Vol. 11, Iss. 8, pp. 1865-1865
Open Access | Times Cited: 7
Machine learning for electric energy consumption forecasting: Application to the Paraguayan system
Félix Morales-Mareco, Miguel García-Torres, Federico Divina, et al.
Logic Journal of IGPL (2024)
Closed Access | Times Cited: 2
Daily PM10, periodicity and harmonic regression model: The case of London
Yasin Okkaoğlu, Yılmaz Akdi, Kamil Demirberk Ünlü
Atmospheric Environment (2020) Vol. 238, pp. 117755-117755
Closed Access | Times Cited: 19
A Novel Deep Reinforcement Approach for IIoT Microgrid Energy Management Systems
Aicha Dridi, Hossam Afifi, Hassine Moungla, et al.
IEEE Transactions on Green Communications and Networking (2021) Vol. 6, Iss. 1, pp. 148-159
Closed Access | Times Cited: 17
Periodicity in precipitation and temperature for monthly data of Turkey
Yılmaz Akdi, Kamil Demirberk Ünlü
Theoretical and Applied Climatology (2020) Vol. 143, Iss. 3-4, pp. 957-968
Closed Access | Times Cited: 16
Modeling and forecasting of monthly PM2.5 emission of Paris by periodogram-based time series methodology
Yılmaz Akdi, Elif Gölveren, Kamil Demirberk Ünlü, et al.
Environmental Monitoring and Assessment (2021) Vol. 193, Iss. 10
Closed Access | Times Cited: 15
Identifying the cycles in COVID-19 infection: the case of Turkey
Yılmaz Akdi, Yunus Emre Karamanoğlu, Kamil Demirberk Ünlü, et al.
Journal of Applied Statistics (2022) Vol. 50, Iss. 11-12, pp. 2360-2372
Open Access | Times Cited: 9
Electricity Consumption Prediction in an Electronic System Using Artificial Neural Networks
Miona Andrejević Stošović, Novak Radivojević, Malinka Ivanova
Electronics (2022) Vol. 11, Iss. 21, pp. 3506-3506
Open Access | Times Cited: 9
A hybrid deep learning methodology for wind power forecasting based on attention
Yıldırım Akbal, Kamil Demirberk Ünlü
International Journal of Green Energy (2024), pp. 1-10
Closed Access | Times Cited: 1
Solar Self-Sufficient Households as a Driving Factor for Sustainability Transformation
Franz H. Harke, Philipp Otto
Sustainability (2023) Vol. 15, Iss. 3, pp. 2734-2734
Open Access | Times Cited: 3
Partially Linear Component Support Vector Machine for Primary Energy Consumption Forecasting of the Electric Power Sector in the United States
Xin Ma, Yubin Cai, Yuan Hong, et al.
Sustainability (2023) Vol. 15, Iss. 9, pp. 7086-7086
Open Access | Times Cited: 2
Forecasting Electricity Consumption Using Exponential Smoothing Methods
Megat Muhammad Afif Megat Muainuddin, Noratikah Abu
(2023) Vol. 1, pp. 320-326
Open Access | Times Cited: 2
A novel grey power-Markov model for the prediction of China’s electricity consumption
Liqin Sun, Youlong Yang, Tong Ning, et al.
Environmental Science and Pollution Research (2021) Vol. 29, Iss. 15, pp. 21717-21738
Open Access | Times Cited: 5
A new approach to modeling cycles with summer and winter demand peaks as input variables for deep neural networks
Tomasz Jasiński
Renewable and Sustainable Energy Reviews (2022) Vol. 159, pp. 112217-112217
Closed Access | Times Cited: 3
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