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# Deep Reinforcement Learning for Real-Time Airfoil Shape Optimization via Integrated CFD-ML Surrogate Modeling Abstract: This paper presents a novel methodology for real-time airfoil shape optimization, utilizing deep reinforcement learning (DRL) coupled with a computationally efficient CFD-ML surrogate modeling framework. The method addresses the critical bottleneck of high computational cost in...
Deep Reinforcement Learning for Real-Time Airfoil Shape Optimization via Integrated CFD-ML
Nov 02, 2025
132 Vues
# Deep Reinforcement Learning for Optimal Grid-Interactive Inverter Control Under Stochastic Renewable Energy Input Abstract: This paper presents a novel deep reinforcement learning (DRL) framework for optimizing the control strategies of grid-interactive inverters (GIIs) operating within complex power grids with high penetrations of stochastic renewable energy sources (RES). Existing GII control ...
Deep Reinforcement Learning for Optimal Grid-Interactive Inverter Control Under Stochastic
Nov 02, 2025
133 Vues
# Bayesian Deep Variational Autoencoder for Uncertainty-Aware Anomaly Detection in Time Series Data Abstract: This paper introduces a novel Bayesian Deep Variational Autoencoder (BDVAE) framework for anomaly detection in time series data, specifically designed to quantify and leverage uncertainty inherent in both the learned model and the data itself. Unlike traditional anomaly detection methods t...
Bayesian Deep Variational Autoencoder for Uncertainty-Aware Anomaly Detection in Time Seri
Nov 02, 2025
131 Vues