This repository contains the implementation of an LSTM-based simulator designed to accelerate reinforcement learning for HVAC systems. The LSTM model is trained to replicate the behavior of the ...

The variation of data includes the variation in weights of rolling stock, speed of rolling stock, and track characteristics (straight, curve, and spiral). The operational uncertainties are included in ...

EvoRL is a fully GPU-accelerated framework for Evolutionary Reinforcement Learning, implemented with JAX. It supports Reinforcement Learning (RL), Evolutionary Computation (EC), Evolution-guided ...

Traditional methods often struggle to account for the intricate dependencies and temporal patterns present in energy stock data. To address these limitations, this study introduces a hybrid model that ...

Since RSUs collect a large volume of data but have limited ... we first apply a Long Short-Term Memory (LSTM) model to predict and update the neighbors for each node while considering effect values, ...

This research endeavors to advance peak load forecasting strategies and demand response optimization at the microgrid level, thereby enhancing grid reliability through the application of Deep ...

Find investment ideas for your portfolio with the latest stock picks from Barron’s below ... our best ideas based on original reporting and data analysis, free from conflicts of interest ...

The significance of AI Artificial intelligence plays a big role in modern crisis prevention across various industries. In ...