Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Dual-stage attention-based long-short-term memory neural networks for energy demand prediction
Jieyang Peng, Andreas Kimmig, Jiahai Wang, et al.
Energy and Buildings (2021) Vol. 249, pp. 111211-111211
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Developing urban building energy models for shanghai city with multi-source open data
Chengcheng Song, Deng Zhang, Zhao Wen-xian, et al.
Sustainable Cities and Society (2024) Vol. 106, pp. 105425-105425
Closed Access | Times Cited: 32
Development and application of an evolutionary deep learning framework of LSTM based on improved grasshopper optimization algorithm for short-term load forecasting
Haowen Hu, Xin Xia, Yuanlin Luo, et al.
Journal of Building Engineering (2022) Vol. 57, pp. 104975-104975
Closed Access | Times Cited: 54
Research trends, themes, and insights on artificial neural networks for smart cities towards SDG-11
Akshat Jain, Ivan Henderson V. Gue, Prateek Jain
Journal of Cleaner Production (2023) Vol. 412, pp. 137300-137300
Open Access | Times Cited: 36
Application of the hybrid neural network model for energy consumption prediction of office buildings
Lize Wang, Dong Xie, Lifeng Zhou, et al.
Journal of Building Engineering (2023) Vol. 72, pp. 106503-106503
Closed Access | Times Cited: 33
Uncertainty management in electricity demand forecasting with machine learning and ensemble learning: Case studies of COVID-19 in the US metropolitans
Mohammed Rashad Baker, Kamal H. Jihad, Hussein Al-bayaty, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106350-106350
Closed Access | Times Cited: 25
Transfer learning integrating similarity analysis for short-term and long-term building energy consumption prediction
Zhuoqun Xing, Yiqun Pan, Yiting Yang, et al.
Applied Energy (2024) Vol. 365, pp. 123276-123276
Closed Access | Times Cited: 12
Interpretable Time-Adaptive Transient Stability Assessment Based on Dual-Stage Attention Mechanism
Qifan Chen, Nan Lin, Siqi Bu, et al.
IEEE Transactions on Power Systems (2022) Vol. 38, Iss. 3, pp. 2776-2790
Closed Access | Times Cited: 33
A field study of CO2 and particulate matter characteristics during the transition season in the subway system in Tianjin, China
Jianlin Ren, Junjie He, Xiangfei Kong, et al.
Energy and Buildings (2021) Vol. 254, pp. 111620-111620
Closed Access | Times Cited: 37
Time-series prediction of hourly atmospheric pressure using ANFIS and LSTM approaches
Mehmet Bilgili, Akın İlhan, Şaban Ünal
Neural Computing and Applications (2022) Vol. 34, Iss. 18, pp. 15633-15648
Closed Access | Times Cited: 19
Perspectives of Machine Learning and Natural Language Processing on Characterizing Positive Energy Districts
Mengjie Han, İlkim Canlı, Juveria Shah, et al.
Buildings (2024) Vol. 14, Iss. 2, pp. 371-371
Open Access | Times Cited: 4
Energy consumption forecasting based on spatio-temporal behavioral analysis for demand-side management
Jieyang Peng, Andreas Kimmig, Dongkun Wang, et al.
Applied Energy (2024) Vol. 374, pp. 124027-124027
Closed Access | Times Cited: 4
Multi-Step Forecasting of Chlorophyll Concentration with Multi-Attention Collaborative Network
Yingying Jin, Feng Zhang, X Q Wang, et al.
Journal of Marine Science and Engineering (2025) Vol. 13, Iss. 1, pp. 151-151
Open Access
A Comparative Analysis of Machine Learning-Based Energy Baseline Models across Multiple Building Types
Jinrong Wu, Su Nguyen, Damminda Alahakoon, et al.
Energies (2024) Vol. 17, Iss. 6, pp. 1285-1285
Open Access | Times Cited: 3
A comparative climate-resilient energy design: Wildfire Resilient Load Forecasting Model using multi-factor deep learning methods
Weijia Yang, Sarah Sparrow, David Wallom
Applied Energy (2024) Vol. 368, pp. 123365-123365
Open Access | Times Cited: 3
Data Attributes in Quality Monitoring of Manufacturing Processes: The Welding Case
Panagiotis Stavropoulos, Alexios Papacharalampopoulos, Kyriakos Sabatakakis
Applied Sciences (2023) Vol. 13, Iss. 19, pp. 10580-10580
Open Access | Times Cited: 7
Power demand estimation techniques applied to microgrid
Katherine Cabana-Jiménez, John E. Candelo-Becerra, Vladimir Sousa Santos, et al.
International Journal of Ambient Energy (2024) Vol. 45, Iss. 1
Closed Access | Times Cited: 2
Machine learning for electric energy consumption forecasting: Application to the Paraguayan system
Félix Morales-Mareco, Miguel García-Torres, Federico Divina, et al.
Logic Journal of IGPL (2024)
Closed Access | Times Cited: 2
FMM-VMD-Transformer: A hybrid deep learning model for predicting natural gas consumption
Xinlei Li, Xiaofu Zou, Jiangfeng Cheng, et al.
Digital engineering. (2024) Vol. 2, pp. 100005-100005
Open Access | Times Cited: 2
Facility location optimization with market segmentation for additive manufacturing material supplier network using quantum annealing
Li Yi, Xiangqian Wu, Jonathan Bauer, et al.
Digital engineering. (2024) Vol. 2, pp. 100011-100011
Open Access | Times Cited: 1
High-precision energy consumption forecasting for large office building using a signal decomposition-based deep learning approach
Chaofan Wang, Kang cheng Liu, Jieyang Peng, et al.
Energy (2024), pp. 133964-133964
Closed Access | Times Cited: 1
Urban monthly power load forecasting based on economy-meteorology-gas demand coupling
Bin Ding, Fan Wang, Chen Chen, et al.
Electrical Engineering (2022) Vol. 104, Iss. 5, pp. 3497-3507
Closed Access | Times Cited: 7
Assessing Residential Building Energy Efficiency Using Evolutionary Dendritic Neural Regression
Zhenyu Song, Yajiao Tang, Shuangbao Song, et al.
Electronics (2024) Vol. 13, Iss. 10, pp. 1803-1803
Open Access
Interpretable deep learning model for load and temperature forecasting: Depending on encoding length, models may be cheating on wrong answers
Wonjun Choi, Sangwon Lee
Energy and Buildings (2023) Vol. 297, pp. 113410-113410
Closed Access | Times Cited: 1
Soybean futures price prediction with dual-stage attention-based long short-term memory: a decomposition and extension approach
Kun Fan, Yanrong Hu, Hongjiu Liu, et al.
Journal of Intelligent & Fuzzy Systems (2023) Vol. 45, Iss. 6, pp. 10579-10602
Closed Access | Times Cited: 1
A Forecast Model of City Natural Gas Daily Load Based on Data Mining
Liang Chen, Jijun Zhang
Scientific Programming (2022) Vol. 2022, pp. 1-14
Open Access | Times Cited: 1
Page 1 - Next Page

Scroll to top