A Differential Privacy-enhanced Federated Learning Method for Short-Term Household Load Forecasting in Smart Grid
Author:
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9674217/9674209/09674514.pdf?arnumber=9674514
Reference21 articles.
1. A Data-Driven Hybrid Optimization Model for Short-Term Residential Load Forecasting
2. A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset
3. Differentially Private Deep Learning for Load Forecasting on Smart Grid
4. Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches †
5. Electrical Load Forecasting Using Edge Computing and Federated Learning
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1. A differential privacy aided DeepFed intrusion detection system for IoT applications;SECURITY AND PRIVACY;2024-07-10
2. Multi-Horizon Short-Term Electrical Load Forecasting: A Comparative Analysis of Statistical Models and Deep Neural Networks;2024 IEEE International Symposium on Measurements & Networking (M&N);2024-07-02
3. Advancing Accuracy in Energy Forecasting using Mixture-of-Experts and Federated Learning;The 15th ACM International Conference on Future and Sustainable Energy Systems;2024-05-31
4. Privacy preserving machine learning in energy services: a survey;Fourth International Conference on Computer Vision and Data Mining (ICCVDM 2023);2024-02-19
5. Advancing Power System Services With Privacy-Preserving Federated Learning Techniques: A Review;IEEE Access;2024
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