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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:

Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms
Puning Xue, Yi Jiang, Zhigang Zhou, et al.
Energy (2019) Vol. 188, pp. 116085-116085
Closed Access | Times Cited: 166

Showing 1-25 of 166 citing articles:

Applications of random forest in multivariable response surface for short-term load forecasting
Guo‐Feng Fan, Liu-Zhen Zhang, Meng Yu, et al.
International Journal of Electrical Power & Energy Systems (2022) Vol. 139, pp. 108073-108073
Closed Access | Times Cited: 140
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: 125
Load forecasting of district heating system based on Informer
Mingju Gong, Yin Zhao, Jiawang Sun, et al.
Energy (2022) Vol. 253, pp. 124179-124179
Closed Access | Times Cited: 114
Short-Term Electricity Load Forecasting with Machine Learning
Ernesto Aguilar Madrid, Nuno António
Information (2021) Vol. 12, Iss. 2, pp. 50-50
Open Access | Times Cited: 110
A multi-energy load forecasting method based on parallel architecture CNN-GRU and transfer learning for data deficient integrated energy systems
Chuang Li, Guojie Li, Keyou Wang, et al.
Energy (2022) Vol. 259, pp. 124967-124967
Closed Access | Times Cited: 103
A comparison of prediction and forecasting artificial intelligence models to estimate the future energy demand in a district heating system
Jason Runge, Étienne Saloux
Energy (2023) Vol. 269, pp. 126661-126661
Closed Access | Times Cited: 47
Energy Forecasting: A Comprehensive Review of Techniques and Technologies
Aristeidis Mystakidis, Paraskevas Koukaras, Nikolaos Tsalikidis, et al.
Energies (2024) Vol. 17, Iss. 7, pp. 1662-1662
Open Access | Times Cited: 27
Explainable district heating load forecasting by means of a reservoir computing deep learning architecture
Adrià Serra Oliver, Alberto Ortiz, Pau Joan Cortés Forteza, et al.
Energy (2025), pp. 134641-134641
Closed Access | Times Cited: 1
A Review of Deep Learning Techniques for Forecasting Energy Use in Buildings
Jason Runge, Radu Zmeureanu
Energies (2021) Vol. 14, Iss. 3, pp. 608-608
Open Access | Times Cited: 76
Integrating feature engineering, genetic algorithm and tree-based machine learning methods to predict the post-accident disability status of construction workers
Kerim Koç, Ömer Ekmekcioğlu, Aslı Pelin Gürgün
Automation in Construction (2021) Vol. 131, pp. 103896-103896
Closed Access | Times Cited: 65
A novel short-term load forecasting framework based on time-series clustering and early classification algorithm
Zhe Chen, Yongbao Chen, Tong Xiao, et al.
Energy and Buildings (2021) Vol. 251, pp. 111375-111375
Closed Access | Times Cited: 56
Principles, research status, and prospects of feature engineering for data-driven building energy prediction: A comprehensive review
Zeyu Wang, Lisha Xia, Hongping Yuan, et al.
Journal of Building Engineering (2022) Vol. 58, pp. 105028-105028
Closed Access | Times Cited: 49
An ensemble multi-step M-RMLSSVR model based on VMD and two-group strategy for day-ahead short-term load forecasting
Fang Yuan, Jinxing Che
Knowledge-Based Systems (2022) Vol. 252, pp. 109440-109440
Closed Access | Times Cited: 46
Data augmentation for improving heating load prediction of heating substation based on TimeGAN
Yunfei Zhang, Zhihua Zhou, Junwei Liu, et al.
Energy (2022) Vol. 260, pp. 124919-124919
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: 33
Explainable district heat load forecasting with active deep learning
Yaohui Huang, Yuan Zhao, Zhijin Wang, et al.
Applied Energy (2023) Vol. 350, pp. 121753-121753
Open Access | Times Cited: 25
Deep neural network with empirical mode decomposition and Bayesian optimisation for residential load forecasting
Ashkan Lotfipoor, Sandhya Patidar, David Jenkins
Expert Systems with Applications (2023) Vol. 237, pp. 121355-121355
Open Access | Times Cited: 25
Energy generation forecasting: elevating performance with machine and deep learning
Aristeidis Mystakidis, Evangelia Ntozi, Konstantinos Afentoulis, et al.
Computing (2023) Vol. 105, Iss. 8, pp. 1623-1645
Open Access | Times Cited: 22
Comparison of strategies for multistep-ahead lake water level forecasting using deep learning models
Gang Li, Zhangkang Shu, Miaoli Lin, et al.
Journal of Cleaner Production (2024) Vol. 444, pp. 141228-141228
Closed Access | Times Cited: 12
Accuracy improvement of the load forecasting in the district heating system by the informer-based framework with the optimal step size selection
Ji Zhang, Yuxin Hu, Yonggong Yuan, et al.
Energy (2024) Vol. 291, pp. 130347-130347
Closed Access | Times Cited: 11
Probabilistic state estimation in district heating grids using deep neural network
Gaowei Yi, Xinlin Zhuang, Yan Li
Sustainable Energy Grids and Networks (2024) Vol. 38, pp. 101353-101353
Closed Access | Times Cited: 8
A novel time-series probabilistic forecasting method for multi-energy loads
Xiangmin Xie, Yuhao Ding, Yuanyuan Sun, et al.
Energy (2024) Vol. 306, pp. 132456-132456
Closed Access | Times Cited: 8
Energy futures and spots prices forecasting by hybrid SW-GRU with EMD and error evaluation
Bin Wang, Jun Wang
Energy Economics (2020) Vol. 90, pp. 104827-104827
Closed Access | Times Cited: 66
Multi-Step Short-Term Power Consumption Forecasting Using Multi-Channel LSTM With Time Location Considering Customer Behavior
Xiaorui Shao, Chang Soo Kim
IEEE Access (2020) Vol. 8, pp. 125263-125273
Open Access | Times Cited: 57
Development of the heating load prediction model for the residential building of district heating based on model calibration
Qiang Zhang, Zhe Tian, Zhijun Ma, et al.
Energy (2020) Vol. 205, pp. 117949-117949
Closed Access | Times Cited: 53
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