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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:

Deep Federated Adaptation: An Adaptative Residential Load Forecasting Approach with Federated Learning
Yuan Shi, Xianze Xu
Sensors (2022) Vol. 22, Iss. 9, pp. 3264-3264
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Federated Learning for Privacy-Preserving: A Review of PII Data Analysis in Fintech
Bibhu Dash, Pawankumar Sharma, Azad Ali
International Journal of Software Engineering & Applications (2022) Vol. 13, Iss. 4, pp. 1-13
Open Access | Times Cited: 89
A federated learning model with the whale optimization algorithm for renewable energy prediction
Viorica Rozina Chifu, Tudor Cioara, Cristian Daniel Anitei, et al.
Computers & Electrical Engineering (2025) Vol. 123, pp. 110259-110259
Open Access | Times Cited: 1
Privacy-preserving federated learning for residential short-term load forecasting
Joaquín Delgado Fernández, Sergio Potenciano Menci, Chul Min Lee, et al.
Applied Energy (2022) Vol. 326, pp. 119915-119915
Open Access | Times Cited: 66
FedMicro-IDA: A federated learning and microservices-based framework for IoT data analytics
Safa Ben Atitallah, Maha Driss, Henda Ben Ghézala
Internet of Things (2023) Vol. 23, pp. 100845-100845
Closed Access | Times Cited: 22
A Comprehensive Survey on Load Forecasting Hybrid Models: Navigating the Futuristic Demand Response Patterns through Experts and Intelligent Systems
Kinza Fida, Usman Abbasi, Muhammad Adnan, et al.
Results in Engineering (2024) Vol. 23, pp. 102773-102773
Open Access | Times Cited: 7
Consumers profiling based federated learning approach for energy load forecasting
Atharvan Dogra, Ashima Anand, Jatin Bedi
Sustainable Cities and Society (2023) Vol. 98, pp. 104815-104815
Closed Access | Times Cited: 21
An adaptive federated learning system for community building energy load forecasting and anomaly prediction
Rui Wang, Hongguang Yun, Rakiba Rayhana, et al.
Energy and Buildings (2023) Vol. 295, pp. 113215-113215
Closed Access | Times Cited: 20
Federated transfer learning with orchard-optimized Conv-SGRU: A novel approach to secure and accurate photovoltaic power forecasting
Syed Muhammad Salman Bukhari, Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar, et al.
Renewable energy focus (2023) Vol. 48, pp. 100520-100520
Open Access | Times Cited: 16
Resilient Electricity Load Forecasting Network with Collective Intelligence Predictor for Smart Cities
Mohd Hafizuddin Bin Kamilin, Shingo Yamaguchi
Electronics (2024) Vol. 13, Iss. 4, pp. 718-718
Open Access | Times Cited: 6
A review of federated learning in renewable energy applications: Potential, challenges, and future directions
Albin Grataloup, Stefan Jonas, Angela Meyer
Energy and AI (2024) Vol. 17, pp. 100375-100375
Open Access | Times Cited: 6
Cyberattack detection for electricity theft in smart grids via stacking ensemble GRU optimization algorithm using federated learning framework
Jun Wang, Yifei Si, Yonghai Zhu, et al.
International Journal of Electrical Power & Energy Systems (2024) Vol. 157, pp. 109848-109848
Open Access | Times Cited: 4
A federated and transfer learning based approach for households load forecasting
Gurjot Singh, Jatin Bedi
Knowledge-Based Systems (2024) Vol. 299, pp. 111967-111967
Closed Access | Times Cited: 4
Advancing Power System Services With Privacy-Preserving Federated Learning Techniques: A Review
Ran Zheng, Andreas Sumper, Mònica Aragüés‐Peñalba, et al.
IEEE Access (2024) Vol. 12, pp. 76753-76780
Open Access | Times Cited: 4
Centralised vs. Decentralised Federated Load Forecasting: Who Holds the Key to Adversarial Attack Robustness?
Habib Ullah Manzoor, Sajjad Hussain, David Flynn, et al.
(2024)
Open Access | Times Cited: 4
Adaptive single-layer aggregation framework for energy-efficient and privacy-preserving load forecasting in heterogeneous Federated smart grids
Habib Ullah Manzoor, Atif Jafri, Ahmed Zoha
Internet of Things (2024), pp. 101376-101376
Open Access | Times Cited: 4
A blockchain-based framework for federated learning with privacy preservation in power load forecasting
Qifan Mao, Liangliang Wang, Long Yu, et al.
Knowledge-Based Systems (2023) Vol. 284, pp. 111338-111338
Closed Access | Times Cited: 11
Personalized federated learning for buildings energy consumption forecasting
Rui Wang, Ling Bai, Rakiba Rayhana, et al.
Energy and Buildings (2024), pp. 114762-114762
Closed Access | Times Cited: 3
Centralised vs. decentralised federated load forecasting in smart buildings: Who holds the key to adversarial attack robustness?
Habib Ullah Manzoor, Sajjad Hussain, David Flynn, et al.
Energy and Buildings (2024) Vol. 324, pp. 114871-114871
Open Access | Times Cited: 3
Differential Private Federated Learning in Geographically Distributed Public Administration Processes
Mirwais Ahmadzai, Giang Nguyen
Future Internet (2024) Vol. 16, Iss. 7, pp. 220-220
Open Access | Times Cited: 2
Exploring the Comprehensive Integration of Artificial Intelligence in Optimizing HVAC System Operations: A Review and Future Outlook
Shengze Lu, Shiyu Zhou, Yan Ding, et al.
Results in Engineering (2024), pp. 103765-103765
Open Access | Times Cited: 2
Short-term forecasting of building cooling load based on data integrity judgment and feature transfer
Yan Ding, Chen Huang, Kuixing Liu, et al.
Energy and Buildings (2023) Vol. 283, pp. 112826-112826
Closed Access | Times Cited: 6
Residential Load Forecasting Using Modified Federated Learning Algorithm
Keon-Jun Park, Sung-Yong Son
IEEE Access (2023) Vol. 11, pp. 40675-40691
Open Access | Times Cited: 5
Comparative Analysis of Data-Driven Algorithms for Building Energy Planning via Federated Learning
Mazhar Ali, Ankit Kumar Singh, Ajit Kumar, et al.
Energies (2023) Vol. 16, Iss. 18, pp. 6517-6517
Open Access | Times Cited: 4
Adaptive DFL‐based straggler mitigation mechanism for synchronous ring topology in digital twin networks
Qazi Waqas Khan, Chan‐Won Park, Rashid Ahmad, et al.
IET Collaborative Intelligent Manufacturing (2024) Vol. 6, Iss. 3
Open Access | Times Cited: 1
Advancing Electric Load Forecasting: Leveraging Federated Learning for Distributed, Non-Stationary, and Discontinuous Time Series
Lucas Richter, Steve Lenk, Peter Bretschneider
Smart Cities (2024) Vol. 7, Iss. 4, pp. 2065-2093
Open Access | Times Cited: 1
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