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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:

Fractional ARIMA with an improved cuckoo search optimization for the efficient Short-term power load forecasting
Fei Wu, Carlo Cattani, Wanqing Song, et al.
Alexandria Engineering Journal (2020) Vol. 59, Iss. 5, pp. 3111-3118
Open Access | Times Cited: 94

Showing 1-25 of 94 citing articles:

Short term electricity load forecasting using hybrid prophet-LSTM model optimized by BPNN
Tasarruf Bashir, Haoyong Chen, Muhammad Faizan Tahir, et al.
Energy Reports (2022) Vol. 8, pp. 1678-1686
Open Access | Times Cited: 163
A new paradigm based on Wasserstein Generative Adversarial Network and time-series graph for integrated energy system forecasting
Zhirui Tian, Gai Mei
Energy Conversion and Management (2025) Vol. 326, pp. 119484-119484
Closed Access | Times Cited: 2
Multifractal Applications in Hydro-Climatology: A Comprehensive Review of Modern Methods
Shamseena Vahab, S. Adarsh
Fractal and Fractional (2025) Vol. 9, Iss. 1, pp. 27-27
Open Access | Times Cited: 1
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
Multivariate machine learning algorithms for energy demand forecasting and load behavior analysis
Farhan Hussain, M. Hasanuzzaman, Nasrudin Abd Rahim
Energy Conversion and Management X (2025), pp. 100903-100903
Open Access | Times Cited: 1
Electrical load forecasting: A deep learning approach based on K-nearest neighbors
Yunxuan Dong, Xuejiao Ma, Tonglin Fu
Applied Soft Computing (2020) Vol. 99, pp. 106900-106900
Closed Access | Times Cited: 110
Short-Term Load Forecasting Using Channel and Temporal Attention Based Temporal Convolutional Network
Xianlun Tang, Hongxu Chen, Wenhao Xiang, et al.
Electric Power Systems Research (2021) Vol. 205, pp. 107761-107761
Closed Access | Times Cited: 97
Improving the Bi-LSTM model with XGBoost and attention mechanism: A combined approach for short-term power load prediction
Yeming Dai, Qiong Zhou, Mingming Leng, et al.
Applied Soft Computing (2022) Vol. 130, pp. 109632-109632
Closed Access | Times Cited: 64
A combined deep learning application for short term load forecasting
İlyas Özer, Serhat Berat Efe, Harun ÖZBAY
Alexandria Engineering Journal (2021) Vol. 60, Iss. 4, pp. 3807-3818
Open Access | Times Cited: 60
Load forecasting via Grey Model-Least Squares Support Vector Machine model and spatial-temporal distribution of electric consumption intensity
Zhenyu Zhao, Yao Zhang, Yujia Yang, et al.
Energy (2022) Vol. 255, pp. 124468-124468
Closed Access | Times Cited: 38
Data-driven short term load forecasting with deep neural networks: Unlocking insights for sustainable energy management
Waqar Waheed, Qingshan Xu
Electric Power Systems Research (2024) Vol. 232, pp. 110376-110376
Closed Access | Times Cited: 9
An ensemble-based approach for short-term load forecasting for buildings with high proportion of renewable energy sources
Abrar Shahriar Pramanik, Saeed Sepasi, Tung Lam Nguyen, et al.
Energy and Buildings (2024) Vol. 308, pp. 113996-113996
Closed Access | Times Cited: 8
Combined electricity load-forecasting system based on weighted fuzzy time series and deep neural networks
Zhining Cao, Jianzhou Wang, Yurui Xia
Engineering Applications of Artificial Intelligence (2024) Vol. 132, pp. 108375-108375
Closed Access | Times Cited: 8
Research and application of a hybrid model for mid-term power demand forecasting based on secondary decomposition and interval optimization
Dongxiao Niu, Zhengsen Ji, Wanying Li, et al.
Energy (2021) Vol. 234, pp. 121145-121145
Closed Access | Times Cited: 53
A three-stage framework for vertical carbon price interval forecast based on decomposition–integration method
Zhengsen Ji, Dongxiao Niu, Mingyu Li, et al.
Applied Soft Computing (2021) Vol. 116, pp. 108204-108204
Closed Access | Times Cited: 50
A novel decomposition-ensemble forecasting system for dynamic dispatching of smart grid with sub-model selection and intelligent optimization
Jianzhou Wang, Lifang Zhang, Zhenkun Liu, et al.
Expert Systems with Applications (2022) Vol. 201, pp. 117201-117201
Closed Access | Times Cited: 32
Hybridization of statistical machine learning and numerical models for improving beam, diffuse and global solar radiation prediction
Samuel Chukwujindu Nwokolo, Anthony Umunnakwe Obiwulu, Julie C. Ogbulezie, et al.
Cleaner Engineering and Technology (2022) Vol. 9, pp. 100529-100529
Open Access | Times Cited: 31
Electric load prediction based on a novel combined interval forecasting system
Jianzhou Wang, Jialu Gao, Danxiang Wei
Applied Energy (2022) Vol. 322, pp. 119420-119420
Closed Access | Times Cited: 29
Short-Term Load Forecasting Based on the CEEMDAN-Sample Entropy-BPNN-Transformer
Shichao Huang, Jing Zhang, Yu He, et al.
Energies (2022) Vol. 15, Iss. 10, pp. 3659-3659
Open Access | Times Cited: 28
An Improved WOA (Whale Optimization Algorithm)-Based CNN-BIGRU-CBAM Model and Its Application to Short-Term Power Load Forecasting
Lei Dai, Haiying Wang
Energies (2024) Vol. 17, Iss. 11, pp. 2559-2559
Open Access | Times Cited: 7
Short-term wind power forecasting based on multi-scale receptive field-mixer and conditional mixture copula
Jinchang Li, Jiapeng Chen, Z. Q. Chen, et al.
Applied Soft Computing (2024) Vol. 164, pp. 112007-112007
Closed Access | Times Cited: 5
Multi-energy load forecasting for small-sample integrated energy systems based on neural network Gaussian process and multi-task learning
Wei Zhang, Yi Cai, Hongyi Zhan, et al.
Energy Conversion and Management (2024) Vol. 321, pp. 119027-119027
Closed Access | Times Cited: 5
Combining MFAC with an improved cuckoo algorithm for flexible robotic rotary arm joint control
Song Liu
International Journal of Intelligent Robotics and Applications (2025)
Closed Access
LSTM vs. Prophet: Achieving Superior Accuracy in Dynamic Electricity Demand Forecasting
Saleh Albahli
Energies (2025) Vol. 18, Iss. 2, pp. 278-278
Open Access
Mitigating concept drift challenges in evolving smart grids: An adaptive ensemble LSTM for enhanced load forecasting
Abdul Azeem, Idris Ismail, Syed Sheeraz Mohani, et al.
Energy Reports (2025) Vol. 13, pp. 1369-1383
Closed Access
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