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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:

A Short-Term Load Forecasting Method Using Integrated CNN and LSTM Network
Shafiul Hasan Rafi, Nahid‐Al Masood, Shohana Rahman Deeba, et al.
IEEE Access (2021) Vol. 9, pp. 32436-32448
Open Access | Times Cited: 311

Showing 1-25 of 311 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: 164
District heater load forecasting based on machine learning and parallel CNN-LSTM attention
Won Hee Chung, Yeong Hyeon Gu, Seong Joon Yoo
Energy (2022) Vol. 246, pp. 123350-123350
Open Access | Times Cited: 129
Robust framework based on hybrid deep learning approach for short term load forecasting of building electricity demand
Charan Sekhar, Ratna Dahiya
Energy (2023) Vol. 268, pp. 126660-126660
Closed Access | Times Cited: 111
Load Forecasting Models in Smart Grid Using Smart Meter Information: A Review
Fanidhar Dewangan, Almoataz Y. Abdelaziz, Monalisa Biswal
Energies (2023) Vol. 16, Iss. 3, pp. 1404-1404
Open Access | Times Cited: 72
Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review
Faiaz Ahsan, Nazia Hasan Dana, Subrata K. Sarker, et al.
Protection and Control of Modern Power Systems (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 58
Comparing Long Short-Term Memory (LSTM) and bidirectional LSTM deep neural networks for power consumption prediction
Davi Guimarães da Silva, Anderson Alvarenga de Moura Meneses
Energy Reports (2023) Vol. 10, pp. 3315-3334
Open Access | Times Cited: 57
Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead
Saima Akhtar, Sulman Shahzad, Asad Zaheer, et al.
Energies (2023) Vol. 16, Iss. 10, pp. 4060-4060
Open Access | Times Cited: 50
Short-term electrical load forecasting using hybrid model of manta ray foraging optimization and support vector regression
Siwei Li, Xiangyu Kong, Yue Liang, et al.
Journal of Cleaner Production (2023) Vol. 388, pp. 135856-135856
Closed Access | Times Cited: 43
Short-term power load forecasting based on AC-BiLSTM model
Fang Liu, Liang Chen
Energy Reports (2024) Vol. 11, pp. 1570-1579
Open Access | Times Cited: 23
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: 4
BE-LSTM: An LSTM-Based Framework for Feature Selection and Building Electricity Consumption Prediction on Small Datasets
Weihao Wang, Hajime Shimakawa, Bo Jie, et al.
Journal of Building Engineering (2025), pp. 111910-111910
Closed Access | Times Cited: 2
Transformer-Based Model for Electrical Load Forecasting
Alexandra L’Heureux, Katarina Grolinger, Miriam A. M. Capretz
Energies (2022) Vol. 15, Iss. 14, pp. 4993-4993
Open Access | Times Cited: 64
Machine Learning for Short-Term Load Forecasting in Smart Grids
Bibi Ibrahim, Luis Rabelo, Edgar Gutiérrez-Franco, et al.
Energies (2022) Vol. 15, Iss. 21, pp. 8079-8079
Open Access | Times Cited: 61
Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
S. N. V. Bramareswara Rao, Y. V. Pavan Kumar, Kottala Padma, et al.
Energies (2022) Vol. 15, Iss. 17, pp. 6124-6124
Open Access | Times Cited: 57
An ensemble framework for short-term load forecasting based on parallel CNN and GRU with improved ResNet
Heng Hua, Mingping Liu, Yuqin Li, et al.
Electric Power Systems Research (2022) Vol. 216, pp. 109057-109057
Closed Access | Times Cited: 49
A novel short receptive field based dilated causal convolutional network integrated with Bidirectional LSTM for short-term load forecasting
Umar Javed, Khalid Ijaz, Muhammad Jawad, et al.
Expert Systems with Applications (2022) Vol. 205, pp. 117689-117689
Closed Access | Times Cited: 43
A Novel Temporal Feature Selection Based LSTM Model for Electrical Short-Term Load Forecasting
Khalid Ijaz, Zawar Hussain, Jameel Ahmad, et al.
IEEE Access (2022) Vol. 10, pp. 82596-82613
Open Access | Times Cited: 42
Load Forecasting with Machine Learning and Deep Learning Methods
Moisés Cordeiro-Costas, Daniel Villanueva, Pablo Eguía, et al.
Applied Sciences (2023) Vol. 13, Iss. 13, pp. 7933-7933
Open Access | Times Cited: 41
Short-term load forecasting using neural networks and global climate models: An application to a large-scale electrical power system
Lucas Barros Scianni Morais, Giancarlo Áquila, Victor Augusto Durães de Faria, et al.
Applied Energy (2023) Vol. 348, pp. 121439-121439
Closed Access | Times Cited: 39
District heating load forecasting with a hybrid model based on LightGBM and FB-prophet
Asim Shakeel, Daotong Chong, Jinshi Wang
Journal of Cleaner Production (2023) Vol. 409, pp. 137130-137130
Closed Access | Times Cited: 36
Deep learning methods utilization in electric power systems
Saima Akhtar, Muhammad Adeel, Muhammad Iqbal, et al.
Energy Reports (2023) Vol. 10, pp. 2138-2151
Open Access | Times Cited: 33
An Efficient Artificial Intelligence Energy Management System for Urban Building Integrating Photovoltaic and Storage
Enrico Giglio, Gabriele Luzzani, Vito Terranova, et al.
IEEE Access (2023) Vol. 11, pp. 18673-18688
Open Access | Times Cited: 32
DA-LSTM: A dynamic drift-adaptive learning framework for interval load forecasting with LSTM networks
Firas Bayram, Phil Aupke, Bestoun S. Ahmed, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106480-106480
Open Access | Times Cited: 30
An Ensemble Framework for Short-Term Load Forecasting Based on TimesNet and TCN
Chuanhui Zuo, Jialong Wang, Mingping Liu, et al.
Energies (2023) Vol. 16, Iss. 14, pp. 5330-5330
Open Access | Times Cited: 27
AI-oriented Smart Power System Transient Stability: The Rationality, Applications, Challenges and Future Opportunities
Wanying Guo, Nawab Muhammad Faseeh Qureshi, Muhammad Aslam Jarwar, et al.
Sustainable Energy Technologies and Assessments (2023) Vol. 56, pp. 102990-102990
Open Access | Times Cited: 23
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