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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 spatial-temporal layer-wise relevance propagation method for improving interpretability and prediction accuracy of LSTM building energy prediction
Guannan Li, Fan Li, Chengliang Xu, et al.
Energy and Buildings (2022) Vol. 271, pp. 112317-112317
Closed Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Interpretable machine learning for building energy management: A state-of-the-art review
Zhe Chen, Fu Xiao, Fangzhou Guo, et al.
Advances in Applied Energy (2023) Vol. 9, pp. 100123-100123
Open Access | Times Cited: 153
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: 45
Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
Van Nhanh Nguyen, W. Tarełko, Prabhakar Sharma, et al.
Energy & Fuels (2024) Vol. 38, Iss. 3, pp. 1692-1712
Closed Access | Times Cited: 45
Interpretation of convolutional neural network-based building HVAC fault diagnosis model using improved layer-wise relevance propagation
Guannan Li, Luhan Wang, Limei Shen, et al.
Energy and Buildings (2023) Vol. 286, pp. 112949-112949
Closed Access | Times Cited: 43
A compound approach for ten-day runoff prediction by coupling wavelet denoising, attention mechanism, and LSTM based on GPU parallel acceleration technology
Yiyang Wang, Wenchuan Wang, Dongmei Xu, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 2, pp. 1281-1299
Closed Access | Times Cited: 16
A hybrid forecasting method for cooling load in large public buildings based on improved long short term memory
Zongyi Liu, Junqi Yu, Chunyong Feng, et al.
Journal of Building Engineering (2023) Vol. 76, pp. 107238-107238
Closed Access | Times Cited: 25
Short-term cooling and heating loads forecasting of building district energy system based on data-driven models
Hanfei Yu, Fan Zhong, Yuji Du, et al.
Energy and Buildings (2023) Vol. 298, pp. 113513-113513
Closed Access | Times Cited: 25
A Review of Data-Driven Building Energy Prediction
Huiheng Liu, Jin Rui Liang, Yanchen Liu, et al.
Buildings (2023) Vol. 13, Iss. 2, pp. 532-532
Open Access | Times Cited: 24
An explainable multiscale LSTM model with wavelet transform and layer-wise relevance propagation for daily streamflow forecasting
Lizhi Tao, Zhichao Cui, Yufeng He, et al.
The Science of The Total Environment (2024) Vol. 929, pp. 172465-172465
Closed Access | Times Cited: 11
Fault diagnosis for cross-building energy systems based on transfer learning and model interpretation
Liang Chen, Guannan Li, Jiangyan Liu, et al.
Journal of Building Engineering (2024) Vol. 91, pp. 109424-109424
Closed Access | Times Cited: 11
Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings
M. Arun, Thanh Tuan Le, Debabrata Barik, et al.
Case Studies in Thermal Engineering (2024), pp. 105115-105115
Open Access | Times Cited: 8
BO-STA-LSTM: Building energy prediction based on a Bayesian Optimized Spatial-Temporal Attention enhanced LSTM method
Guannan Li, Yong Wang, Chengliang Xu, et al.
Developments in the Built Environment (2024) Vol. 18, pp. 100465-100465
Open Access | Times Cited: 7
Short-term building energy consumption prediction strategy based on modal decomposition and reconstruction algorithm
Yinghao Jiao, Zhi Tan, De Zhang, et al.
Energy and Buildings (2023) Vol. 290, pp. 113074-113074
Closed Access | Times Cited: 16
Comprehensive transferability assessment of short-term cross-building-energy prediction using deep adversarial network transfer learning
Guannan Li, Yubei Wu, Sungmin Yoon, et al.
Energy (2024) Vol. 299, pp. 131395-131395
Closed Access | Times Cited: 6
A Future Direction of Machine Learning for Building Energy Management: Interpretable Models
Luca Gugliermetti, Fabrizio Cumo, Sofia Agostinelli
Energies (2024) Vol. 17, Iss. 3, pp. 700-700
Open Access | Times Cited: 5
Developing a dual-modal surrogate model training framework for building performance prediction in early design stage
Zhen Han, Gang Liu, Lihua Zhang, et al.
Energy and Buildings (2025), pp. 115307-115307
Closed Access
Automated data-driven building energy load prediction method based on generative pre-trained transformers (GPT)
Chaobo Zhang, Jian Zhang, Yang Zhao, et al.
Energy (2025), pp. 134824-134824
Closed Access
Performance evaluation of short-term cross-building energy predictions using deep transfer learning strategies
Guannan Li, Yubei Wu, Jiangyan Liu, et al.
Energy and Buildings (2022) Vol. 275, pp. 112461-112461
Closed Access | Times Cited: 25
Validation of virtual sensor-assisted Bayesian inference-based in-situ sensor calibration strategy for building HVAC systems
Guannan Li, Jiahao Xiong, Shaobo Sun, et al.
Building Simulation (2022) Vol. 16, Iss. 2, pp. 185-203
Closed Access | Times Cited: 22
Interpretation and explanation of convolutional neural network-based fault diagnosis model at the feature-level for building energy systems
Guannan Li, Liang Chen, Cheng Fan, et al.
Energy and Buildings (2023) Vol. 295, pp. 113326-113326
Closed Access | Times Cited: 12
Enhancing Energy Efficiency and Building Performance through BEMS-BIM Integration
Mária Kozlovská, Stefan Petkanic, František Vranay, et al.
Energies (2023) Vol. 16, Iss. 17, pp. 6327-6327
Open Access | Times Cited: 12
An improved transfer learning strategy for short-term cross-building energy prediction using data incremental
Guannan Li, Yubei Wu, Chengchu Yan, et al.
Building Simulation (2023) Vol. 17, Iss. 1, pp. 165-183
Closed Access | Times Cited: 12
Performance assessment of cross office building energy prediction in the same region using the domain adversarial transfer learning strategy
Guannan Li, Zixi Wang, Jiajia Gao, et al.
Applied Thermal Engineering (2024) Vol. 241, pp. 122357-122357
Closed Access | Times Cited: 4
Interpretable Data-Driven Methods for Building Energy Modelling—A Review of Critical Connections and Gaps
Massimiliano Manfren, Karla M. Gonzalez-Carreon, P.A.B. James
Energies (2024) Vol. 17, Iss. 4, pp. 881-881
Open Access | Times Cited: 4
An interpretable graph convolutional neural network based fault diagnosis method for building energy systems
Guannan Li, Zhanpeng Yao, Liang Chen, et al.
Building Simulation (2024) Vol. 17, Iss. 7, pp. 1113-1136
Closed Access | Times Cited: 4
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