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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:

Experimental investigation of variational mode decomposition and deep learning for short-term multi-horizon residential electric load forecasting
Mohamed Aymane Ahajjam, Daniel Bonilla Licea, Mounir Ghogho, et al.
Applied Energy (2022) Vol. 326, pp. 119963-119963
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

On the Benefits of Using Metaheuristics in the Hyperparameter Tuning of Deep Learning Models for Energy Load Forecasting
Nebojša Bačanin, Cătălin Stoean, Miodrag Živković, et al.
Energies (2023) Vol. 16, Iss. 3, pp. 1434-1434
Open Access | Times Cited: 78
A comprehensive review on deep learning approaches for short-term load forecasting
Yavuz Eren, İbrahim Beklan Küçükdemiral
Renewable and Sustainable Energy Reviews (2023) Vol. 189, pp. 114031-114031
Open Access | Times Cited: 68
Interpretable building energy consumption forecasting using spectral clustering algorithm and temporal fusion transformers architecture
Peijun Zheng, Heng Zhou, Jiang Liu, et al.
Applied Energy (2023) Vol. 349, pp. 121607-121607
Closed Access | Times Cited: 48
A novel wind power forecasting system integrating time series refining, nonlinear multi-objective optimized deep learning and linear error correction
Jianzhou Wang, Yuansheng Qian, Linyue Zhang, et al.
Energy Conversion and Management (2023) Vol. 299, pp. 117818-117818
Closed Access | Times Cited: 40
A deep learning framework using multi-feature fusion recurrent neural networks for energy consumption forecasting
Lei Fang, Bin He
Applied Energy (2023) Vol. 348, pp. 121563-121563
Closed Access | Times Cited: 34
Dampening energy security-related uncertainties in the United States: The role of green energy-technology investment and operation of transnational corporations
Ojonugwa Usman, Paul Terhemba Iorember, Oktay Özkan, et al.
Energy (2023) Vol. 289, pp. 130006-130006
Open Access | Times Cited: 34
Pulse-diagnosis-inspired multi-feature extraction deep network for short-term electricity load forecasting
Han Wu, Yan Liang, Jiani Heng
Applied Energy (2023) Vol. 339, pp. 120995-120995
Closed Access | Times Cited: 23
Harnessing AI for solar energy: Emergence of transformer models
Muhammad Fainan Hanif, Jianchun Mi
Applied Energy (2024) Vol. 369, pp. 123541-123541
Closed Access | Times Cited: 11
A new intelligent hybrid forecasting method for power load considering uncertainty
Guo‐Feng Fan, Ying-Ying Han, Jingjing Wang, et al.
Knowledge-Based Systems (2023) Vol. 280, pp. 111034-111034
Closed Access | Times Cited: 20
Integrated Approaches in Resilient Hierarchical Load Forecasting via TCN and Optimal Valley Filling Based Demand Response Application
A. Selim Türkoğlu, Burcu Erkmen, Yavuz Eren, et al.
Applied Energy (2024) Vol. 360, pp. 122722-122722
Closed Access | Times Cited: 6
An error-corrected deep Autoformer model via Bayesian optimization algorithm and secondary decomposition for photovoltaic power prediction
Jie Chen, Peng Tian, Shijie Qian, et al.
Applied Energy (2024) Vol. 377, pp. 124738-124738
Closed Access | Times Cited: 5
Feature extraction and an interpretable hierarchical model for annual hourly electricity consumption profile of commercial buildings in China
Hao Li, Yi Dai, Xiaochen Liu, et al.
Energy Conversion and Management (2023) Vol. 291, pp. 117244-117244
Closed Access | Times Cited: 12
Interval Load Forecasting for Users from the Perspective of Interval Aggregation Based on Cluster Identification
Man Jiang, Chaocheng Zhao, Kaishuai Xu, et al.
Lecture notes in electrical engineering (2025), pp. 69-86
Closed Access
Incorporated flexible load forecasting based on non-intrusive load monitoring: a TCN-based meta learning approach
Yun Zhang, Qiang Shu, Feng Ding, et al.
Frontiers in Energy Research (2025) Vol. 13
Open Access
Neural ordinary differential equations-based approach for enhanced building energy modeling on small datasets
Zhihao Ma, Gang Yi Jiang, Jianli Chen
Building Simulation (2025)
Closed Access
Multi-prediction of electric load and photovoltaic solar power in grid-connected photovoltaic system using state transition method
Hu Wang, Lei Mao, Heng Zhang, et al.
Applied Energy (2023) Vol. 353, pp. 122138-122138
Closed Access | Times Cited: 10
Spatio-Temporal Forecasting: A Survey of Data-Driven Models Using Exogenous Data
Safaa Berkani, Bassma Guermah, Mehdi Zakroum, et al.
IEEE Access (2023) Vol. 11, pp. 75191-75214
Open Access | Times Cited: 9
Decomposition prediction fractional-order PID reinforcement learning for short-term smart generation control of integrated energy systems
Linfei Yin, Da Zheng
Applied Energy (2023) Vol. 355, pp. 122246-122246
Closed Access | Times Cited: 9
Advancements in Household Load Forecasting: Deep Learning Model with Hyperparameter Optimization
Hamdi A. Al-Jamimi, Galal M. BinMakhashen, Muhammed Y. Worku, et al.
Electronics (2023) Vol. 12, Iss. 24, pp. 4909-4909
Open Access | Times Cited: 7
A double broad learning approach based on variational modal decomposition for Lithium-Ion battery prognostics
Xiaojia Wang, Xinyue Guo, Sheng Xu, et al.
International Journal of Electrical Power & Energy Systems (2024) Vol. 156, pp. 109764-109764
Open Access | Times Cited: 2
A VMD-deep learning approach for individual load monitoring and forecasting for residential buildings energy management
Ismael Jrhilifa, Hamid Ouadi, Abdelilah Jilbab, et al.
e-Prime - Advances in Electrical Engineering Electronics and Energy (2024) Vol. 8, pp. 100624-100624
Open Access | Times Cited: 2
Electric load forecasting under false data injection attacks via denoising deep learning and generative adversarial networks
Fayezeh Mahmoudnezhad, Arash Moradzadeh, Behnam Mohammadi‐Ivatloo, et al.
IET Generation Transmission & Distribution (2024)
Open Access | Times Cited: 2
Short‐term electrical load forecasting model based on multi‐dimensional meteorological information spatio‐temporal fusion and optimized variational mode decomposition
Ling Yun Wang, Xiang Zhou, Honglei Xu, et al.
IET Generation Transmission & Distribution (2023) Vol. 17, Iss. 20, pp. 4647-4663
Open Access | Times Cited: 5
GRU combined model based on multi-objective optimization for short-term residential load forecasting
Lingzhi Yi, Xinlong Peng, Chaodong Fan, et al.
Journal of Intelligent & Fuzzy Systems (2024) Vol. 46, Iss. 4, pp. 10423-10440
Closed Access
Combined Multi-Component Composite Time Series Power Prediction Model for Distributed Energy Systems Based on Stl Data Decomposition
Tianbo Yang, Shiying He, Xiaojiao Chen, et al.
(2024)
Closed Access
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