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Load Forecasting

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Showing 51–100 of 235 papers

TitleStatusHype
Transfer Learning in Deep Learning Models for Building Load Forecasting: Case of Limited DataCode0
Artificial Intelligence (AI) in Action: Addressing the COVID-19 Pandemic with Natural Language Processing (NLP)—0
Appliance Level Short-term Load Forecasting via Recurrent Neural Network—0
A Global Modeling Approach for Load Forecasting in Distribution Networks—0
Data Selection for Short Term load forecasting—0
An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting—0
DA-LSTM: A Dynamic Drift-Adaptive Learning Framework for Interval Load Forecasting with LSTM Networks—0
A New State-of-the-Art Transformers-Based Load Forecaster on the Smart Grid Domain—0
Deep Learning-Based Cyber-Attack Detection Model for Smart Grids—0
Deep-Learning-Based, Multi-Timescale Load Forecasting in Buildings: Opportunities and Challenges from Research to Deployment—0
Deep Learning for Intelligent Demand Response and Smart Grids: A Comprehensive Survey—0
A generalised multi-factor deep learning electricity load forecasting model for wildfire-prone areas—0
Adaptive model selection in photonic reservoir computing by reinforcement learning—0
Daily peak electrical load forecasting with a multi-resolution approach—0
Crossing Roads of Federated Learning and Smart Grids: Overview, Challenges, and Perspectives—0
A Neural Network-Based Energy Management System for PV-Battery Based Microgrids—0
Cost-Oriented Load Forecasting—0
An Error Correction Mid-term Electricity Load Forecasting Model Based on Seasonal Decomposition—0
Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting—0
Clustering Enabled Few-Shot Load Forecasting—0
Classification of load forecasting studies by forecasting problem to select load forecasting techniques and methodologies—0
An Asymmetric Loss with Anomaly Detection LSTM Framework for Power Consumption Prediction—0
Advancing Long-Term Multi-Energy Load Forecasting with Patchformer: A Patch and Transformer-Based Approach—0
Adaptive Methods for Short-Term Electricity Load Forecasting During COVID-19 Lockdown in France—0
IISE PG&E Energy Analytics Challenge 2025: Hourly-Binned Regression Models Beat Transformers in Load Forecasting—0
Federated Learning with Hyperparameter-based Clustering for Electrical Load Forecasting—0
Characterization of electric consumers through an automated clustering pipeline—0
Analysis of Weather and Time Features in Machine Learning-aided ERCOT Load Forecasting—0
Chance-Constrained AC Optimal Power Flow for Unbalanced Distribution Grids—0
Causal Effect Estimation with Global Probabilistic Forecasting: A Case Study of the Impact of Covid-19 Lockdowns on Energy Demand—0
A multi-source data power load forecasting method using attention mechanism-based parallel cnn-gru—0
Addressing Heterogeneity in Federated Load Forecasting with Personalization Layers—0
Enhancing Microgrid Performance Prediction with Attention-based Deep Learning Models—0
Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting—0
Building Energy Load Forecasting using Deep Neural Networks—0
AMI-FML: A Privacy-Preserving Federated Machine Learning Framework for AMI—0
Electric Vehicle Driver Clustering using Statistical Model and Machine Learning—0
Exploring Lightweight Federated Learning for Distributed Load Forecasting—0
Exploring Physical-Based Constraints in Short-Term Load Forecasting: A Defense Mechanism Against Cyberattack—0
Facilitating AI and System Operator Synergy: Active Learning-Enhanced Digital Twin Architecture for Day-Ahead Load Forecasting—0
Electricity Load Forecasting -- An Evaluation of Simple 1D-CNN Network Structures—0
Federated Learning for Short-term Residential Load Forecasting—0
Block-FeDL: Electric Vehicle Charging Load Forecasting using Federated Learning and Blockchain—0
Federated Short-Term Load Forecasting with Personalization Layers for Heterogeneous Clients—0
FedREP: Towards Horizontal Federated Load Forecasting for Retail Energy Providers—0
Few-Shot Load Forecasting Under Data Scarcity in Smart Grids: A Meta-Learning Approach—0
Forecasting Short-term load using Econometrics time series model with T-student Distribution—0
Forte: An Interactive Visual Analytic Tool for Trust-Augmented Net Load Forecasting—0
Electrical Load Forecasting over Multihop Smart Metering Networks with Federated Learning—0
A Meta-learning based Distribution System Load Forecasting Model Selection Framework—0
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