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Load Forecasting

Papers

Showing 51–75 of 235 papers

TitleStatusHype
Stacking for Probabilistic Short-term Load Forecasting—0
Short-Term Electricity Demand Forecasting of Dhaka City Using CNN with Stacked BiLSTM—0
Few-Shot Load Forecasting Under Data Scarcity in Smart Grids: A Meta-Learning Approach—0
Block-FeDL: Electric Vehicle Charging Load Forecasting using Federated Learning and Blockchain—0
Multiscale Spatio-Temporal Enhanced Short-term Load Forecasting of Electric Vehicle Charging Stations—0
Efficient mid-term forecasting of hourly electricity load using generalized additive modelsCode0
Automated Deep Learning for Load Forecasting—0
Short-term power load forecasting for integrated energy system based on a residual and attentive LSTM-TCN hybrid network—0
A Flow-Based Model for Conditional and Probabilistic Electricity Consumption Profile Generation and PredictionCode0
Advancing Long-Term Multi-Energy Load Forecasting with Patchformer: A Patch and Transformer-Based Approach—0
Some variation of COBRA in sequential learning setup—0
TimeGPT in Load Forecasting: A Large Time Series Model Perspective—0
Exploring Lightweight Federated Learning for Distributed Load Forecasting—0
Addressing Heterogeneity in Federated Load Forecasting with Personalization Layers—0
Electrical Load Forecasting Model Using Hybrid LSTM Neural Networks with Online Correction—0
Privacy-Preserving Collaborative Split Learning Framework for Smart Grid Load ForecastingCode1
Adaptive time series forecasting with markovian variance switching—0
AI-Powered Predictions for Electricity Load in Prosumer Communities—0
DiffPLF: A Conditional Diffusion Model for Probabilistic Forecasting of EV Charging LoadCode1
Interpretable Short-Term Load Forecasting via Multi-Scale Temporal Decomposition—0
Privacy-Preserving Distributed Learning for Residential Short-Term Load ForecastingCode0
E2E-AT: A Unified Framework for Tackling Uncertainty in Task-aware End-to-end LearningCode0
Deep Learning-Based Cyber-Attack Detection Model for Smart Grids—0
Privacy-Preserving Load Forecasting via Personalized Model Obfuscation—0
Load Data Valuation in Multi-Energy Systems: An End-to-End Approach—0
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