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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:

A combined model based on multiple seasonal patterns and modified firefly algorithm for electrical load forecasting
Li‐Ye Xiao, Wei Shao, Tu-Lu Liang, et al.
Applied Energy (2016) Vol. 167, pp. 135-153
Closed Access | Times Cited: 141

Showing 1-25 of 141 citing articles:

Short term electricity load forecasting using a hybrid model
Jinliang Zhang, Yi‐Ming Wei, Dezhi Li, et al.
Energy (2018) Vol. 158, pp. 774-781
Open Access | Times Cited: 273
A Comprehensive Review of the Load Forecasting Techniques Using Single and Hybrid Predictive Models
Abdullah Al Mamun, Md. Sohel, Naeem Mohammad, et al.
IEEE Access (2020) Vol. 8, pp. 134911-134939
Open Access | Times Cited: 252
A seasonal GM(1,1) model for forecasting the electricity consumption of the primary economic sectors
Zheng‐Xin Wang, Qin Li, Ling-Ling Pei
Energy (2018) Vol. 154, pp. 522-534
Closed Access | Times Cited: 243
Computational Intelligence Approaches for Energy Load Forecasting in Smart Energy Management Grids: State of the Art, Future Challenges, and Research Directions
Narjes Fallah, Ravinesh C. Deo, Mohammad Shojafar, et al.
Energies (2018) Vol. 11, Iss. 3, pp. 596-596
Open Access | Times Cited: 222
A novel two-stage forecasting model based on error factor and ensemble method for multi-step wind power forecasting
Hao Yan, Tian Cheng-shi
Applied Energy (2019) Vol. 238, pp. 368-383
Closed Access | Times Cited: 222
Electric load forecasting by complete ensemble empirical mode decomposition adaptive noise and support vector regression with quantum-based dragonfly algorithm
Zichen Zhang, Wei‐Chiang Hong
Nonlinear Dynamics (2019) Vol. 98, Iss. 2, pp. 1107-1136
Closed Access | Times Cited: 195
Application of variational mode decomposition and chaotic grey wolf optimizer with support vector regression for forecasting electric loads
Zichen Zhang, Wei‐Chiang Hong
Knowledge-Based Systems (2021) Vol. 228, pp. 107297-107297
Closed Access | Times Cited: 183
A novel hybrid algorithm for electricity price and load forecasting in smart grids with demand-side management
Ali Ghasemi, Hossein Shayeghi, Mohammad Moradzadeh, et al.
Applied Energy (2016) Vol. 177, pp. 40-59
Closed Access | Times Cited: 173
Hybrid wind energy forecasting and analysis system based on divide and conquer scheme: A case study in China
Wendong Yang, Jianzhou Wang, Haiyan Lu, et al.
Journal of Cleaner Production (2019) Vol. 222, pp. 942-959
Open Access | Times Cited: 149
A hybrid load forecasting model based on support vector machine with intelligent methods for feature selection and parameter optimization
Yeming Dai, Pei Zhao
Applied Energy (2020) Vol. 279, pp. 115332-115332
Closed Access | Times Cited: 141
Load Forecasting Techniques for Power System: Research Challenges and Survey
Naqash Ahmad, Yazeed Yasin Ghadi, Muhammad Adnan, et al.
IEEE Access (2022) Vol. 10, pp. 71054-71090
Open Access | Times Cited: 132
Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges
Peng Lu, Lin Ye, Yongning Zhao, et al.
Applied Energy (2021) Vol. 301, pp. 117446-117446
Closed Access | Times Cited: 129
Ensemble models of TCN-LSTM-LightGBM based on ensemble learning methods for short-term electrical load forecasting
Jianqiang Gong, Zhiguo Qu, Zhiyu Zhu, et al.
Energy (2025), pp. 134757-134757
Closed Access | Times Cited: 1
An improved grey model optimized by multi-objective ant lion optimization algorithm for annual electricity consumption forecasting
Jianzhou Wang, Pei Du, Haiyan Lu, et al.
Applied Soft Computing (2018) Vol. 72, pp. 321-337
Closed Access | Times Cited: 149
A novel fuzzy-based ensemble model for load forecasting using hybrid deep neural networks
George Sideratos, A. Ikonomopoulos, Nikos Hatziargyriou
Electric Power Systems Research (2019) Vol. 178, pp. 106025-106025
Closed Access | Times Cited: 142
Research and application of a combined model based on multi-objective optimization for multi-step ahead wind speed forecasting
Jianzhou Wang, Jiani Heng, Li‐Ye Xiao, et al.
Energy (2017) Vol. 125, pp. 591-613
Closed Access | Times Cited: 120
Long-term load forecasting: models based on MARS, ANN and LR methods
Gamze Nalçacı, Ayşe Özmen, Gerhard‐Wilhelm Weber
Central European Journal of Operations Research (2018) Vol. 27, Iss. 4, pp. 1033-1049
Closed Access | Times Cited: 118
Multi-step wind speed forecasting based on a hybrid forecasting architecture and an improved bat algorithm
Li‐Ye Xiao, Feng Qian, Wei Shao
Energy Conversion and Management (2017) Vol. 143, pp. 410-430
Closed Access | Times Cited: 114
Research and application of a hybrid model based on multi-objective optimization for electrical load forecasting
Li‐Ye Xiao, Wei Shao, Chen Wang, et al.
Applied Energy (2016) Vol. 180, pp. 213-233
Closed Access | Times Cited: 112
A hybrid forecasting model based on date-framework strategy and improved feature selection technology for short-term load forecasting
Ping Jiang, Feng Liu, Yiliao Song
Energy (2016) Vol. 119, pp. 694-709
Closed Access | Times Cited: 112
A hybrid model based on selective ensemble for energy consumption forecasting in China
Jin Xiao, Yuxi Li, Ling Xie, et al.
Energy (2018) Vol. 159, pp. 534-546
Closed Access | Times Cited: 108
Research and application of a hybrid wavelet neural network model with the improved cuckoo search algorithm for electrical power system forecasting
Li‐Ye Xiao, Wei Shao, Mengxia Yu, et al.
Applied Energy (2017) Vol. 198, pp. 203-222
Closed Access | Times Cited: 104
Mixed kernel based extreme learning machine for electric load forecasting
Yanhua Chen, Marius Kloft, Yi Yang, et al.
Neurocomputing (2018) Vol. 312, pp. 90-106
Closed Access | Times Cited: 97
Sequential grid approach based support vector regression for short-term electric load forecasting
Youlong Yang, Jinxing Che, Chengzhi Deng, et al.
Applied Energy (2019) Vol. 238, pp. 1010-1021
Closed Access | Times Cited: 94
A novel decomposition‐ensemble model for forecasting short‐term load‐time series with multiple seasonal patterns
Xiaobo Zhang, Jianzhou Wang
Applied Soft Computing (2018) Vol. 65, pp. 478-494
Closed Access | Times Cited: 92
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