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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:

Transfer learning in demand response: A review of algorithms for data-efficient modelling and control
Thijs Peirelinck, Hussain Kazmi, Brida V. Mbuwir, et al.
Energy and AI (2021) Vol. 7, pp. 100126-100126
Open Access | Times Cited: 68

Showing 26-50 of 68 citing articles:

SolNet: Open-source deep learning models for photovoltaic power forecasting across the globe
Joris Depoortere, Johan Driesen, Johan A. K. Suykens, et al.
International Journal of Forecasting (2025)
Closed Access
Energy balances, thermal performance, and heat stress: Disentangling occupant behaviour and weather influences in a Dutch net-zero energy neighborhood
Hussain Kazmi, Merel Keijsers, Fahad Mehmood, et al.
Energy and Buildings (2022) Vol. 263, pp. 112020-112020
Open Access | Times Cited: 21
How good are TSO load and renewable generation forecasts: Learning curves, challenges, and the road ahead
Hussain Kazmi, Zhenmin Tao
Applied Energy (2022) Vol. 323, pp. 119565-119565
Open Access | Times Cited: 21
Facilitating innovation and knowledge transfer between homogeneous and heterogeneous datasets: Generic incremental transfer learning approach and multidisciplinary studies
Kwok Tai Chui, Varsha Arya, Shahab S. Band, et al.
Journal of Innovation & Knowledge (2023) Vol. 8, Iss. 2, pp. 100313-100313
Open Access | Times Cited: 11
Remote Sensing for Lithology Mapping in Vegetation-Covered Regions: Methods, Challenges, and Opportunities
Yansi Chen, Yunchen Wang, Feng Zhang, et al.
Minerals (2023) Vol. 13, Iss. 9, pp. 1153-1153
Open Access | Times Cited: 11
Energy efficiency and savings analysis with multirate sampling for petrochemical process using convolutional neural network-based transfer learning
Chanin Panjapornpon, Santi Bardeeniz, M.A. Hussain, et al.
Energy and AI (2023) Vol. 14, pp. 100258-100258
Open Access | Times Cited: 10
Dynamic customer demand management: A reinforcement learning model based on real-time pricing and incentives
Eduardo Salazar, Mauricio E. Samper, H. Daniel Patiño
Renewable energy focus (2023) Vol. 46, pp. 39-56
Closed Access | Times Cited: 10
Data-driven heat pump operation strategy using rainbow deep reinforcement learning for significant reduction of electricity cost
Gwangwoo Han, Hong-Jin Joo, Hee-Won Lim, et al.
Energy (2023) Vol. 270, pp. 126913-126913
Closed Access | Times Cited: 9
Image Encoded Time Series Classification of Small Datasets: An Innovative Architecture Using Deep Learning Ensembles
Pubudu L. Indrasiri, Bipasha Kashyap, Pubudu N. Pathirana
Research Square (Research Square) (2024)
Open Access | Times Cited: 3
Early energy performance analysis of smart buildings by consolidated artificial neural network paradigms
Guoqing Guo, Peng Liu, Yuchen Zheng
Heliyon (2024) Vol. 10, Iss. 4, pp. e25848-e25848
Open Access | Times Cited: 3
Comprehensive Sensitivity Analysis Framework for Transfer Learning Performance Assessment for Time Series Forecasting: Basic Concepts and Selected Case Studies
Witesyavwirwa Vianney Kambale, Mohamed Salem, Taha Benarbia, et al.
Symmetry (2024) Vol. 16, Iss. 2, pp. 241-241
Open Access | Times Cited: 3
Explainable deep transfer learning for energy efficiency prediction based on uncertainty detection and identification
Chanin Panjapornpon, Santi Bardeeniz, M.A. Hussain, et al.
Energy and AI (2022) Vol. 12, pp. 100224-100224
Open Access | Times Cited: 14
A Degradation Prediction Method for PEM Fuel Cell Based on Deep Temporal Feature Extraction and Transfer Learning
Yufan Zhang, Rui Ma, Renyou Xie, et al.
IEEE Transactions on Transportation Electrification (2023) Vol. 10, Iss. 1, pp. 203-212
Closed Access | Times Cited: 8
A transfer learning approach to minimize reinforcement learning risks in energy optimization for automated and smart buildings
M. D. Genkin, J.J. McArthur
Energy and Buildings (2023) Vol. 303, pp. 113760-113760
Closed Access | Times Cited: 8
Evaluation of activated sludge settling characteristics from microscopy images with deep convolutional neural networks and transfer learning
Sina Borzooei, Leonardo Scabini, Gisele Miranda, et al.
Journal of Water Process Engineering (2024) Vol. 64, pp. 105692-105692
Open Access | Times Cited: 2
Using Domain-Augmented Federated Learning to Model Thermostatically Controlled Loads
Attila Bálint, Haroon Raja, Johan Driesen, et al.
IEEE Transactions on Smart Grid (2023) Vol. 14, Iss. 5, pp. 4116-4124
Open Access | Times Cited: 5
A Data-Efficient Building Electricity Load Forecasting Method Based on Maximum Mean Discrepancy and Improved TrAdaBoost Algorithm
Kangji Li, Borui Wei, Qianqian Tang, et al.
Energies (2022) Vol. 15, Iss. 23, pp. 8780-8780
Open Access | Times Cited: 8
Enhancing brain tumor classification with transfer learning: Leveraging DenseNet121 for accurate and efficient detection
Asif Raza, Mohammed S. Alshehri, Sultan Almakdi, et al.
International Journal of Imaging Systems and Technology (2023) Vol. 34, Iss. 1
Open Access | Times Cited: 4
Enhanced Sequence-to-Sequence Deep Transfer Learning for Day-Ahead Electricity Load Forecasting
Vasileios Laitsos, Georgios Vontzos, Apostolos Tsiovoulos, et al.
(2024)
Open Access | Times Cited: 1
Enhanced Sequence-to-Sequence Deep Transfer Learning for Day-Ahead Electricity Load Forecasting
Vasileios Laitsos, Georgios Vontzos, Apostolos Tsiovoulos, et al.
Electronics (2024) Vol. 13, Iss. 10, pp. 1996-1996
Open Access | Times Cited: 1
Optimizing Robotic Arm Control Using Deep Q-Learning and Artificial Neural Networks Through Demonstration-Based Methodologies: A Case Study of Dynamic and Static Conditions
Tianci Gao
Robotics and Autonomous Systems (2024) Vol. 181, pp. 104771-104771
Closed Access | Times Cited: 1
Assessing Community Needs in Disasters: Transfer Learning for Fusing Limited Georeferenced Data from Crowdsourced Applications on the Community Level
Christin Salley, Neda Mohammadi, Jiajia Xie, et al.
Journal of Management in Engineering (2024) Vol. 40, Iss. 6
Closed Access | Times Cited: 1
Deep reinforcement learning with planning guardrails for building energy demand response
Doseok Jang, Lucas Spangher, Selvaprabu Nadarajah, et al.
Energy and AI (2022) Vol. 11, pp. 100204-100204
Open Access | Times Cited: 7
Analysis of Neural Networks Used by Artificial Intelligence in the Energy Transition with Renewable Energies
Íñigo Manuel Iglesias-Sanfeliz Cubero, Andrés Meana-Fernández, Juan Carlos Ríos‐Fernández, et al.
Applied Sciences (2023) Vol. 14, Iss. 1, pp. 389-389
Open Access | Times Cited: 4
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning☆
Parvin Malekzadeh, Ming Hou, Konstantinos N. Plataniotis
Neurocomputing (2023) Vol. 530, pp. 165-187
Open Access | Times Cited: 3

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