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Found 6 papers, 1 papers with code
Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging
Results show that the proposed LSTM-BNNs achieve accuracy similar to point forecasts with the advantage of prediction intervals.
Agglomerative Hierarchical Clustering with Dynamic Time Warping for Household Load Curve Clustering
Energy companies often implement various demand response (DR) programs to better match electricity demand and supply by offering the consumers incentives to reduce their demand during critical periods.
Reinforcement Learning Algorithms: An Overview and Classification
The desire to make applications and machines more intelligent and the aspiration to enable their operation without human interaction have been driving innovations in neural networks, deep learning, and other machine learning techniques.
Autonomous Unmanned Aerial Vehicle Navigation using Reinforcement Learning: A Systematic Review
There is an increasing demand for using Unmanned Aerial Vehicle (UAV), known as drones, in different applications such as packages delivery, traffic monitoring, search and rescue operations, and military combat engagements.
Deep Learning for High-Impedance Fault Detection: Convolutional Autoencoders
Contrary to the conventional autoencoders that learn from normal behavior, the convolutional autoencoder (CAE) in CAE-HIFD learns only from the HIF signals eliminating the need for presence of diverse non-HIF scenarios in the CAE training.
ServeNet: A Deep Neural Network for Web Services Classification
Automated service classification plays a crucial role in service discovery, selection, and composition.
