Abstract: The goal of our research is to develop a model that achieves higher accuracy in predicting stock price movements, enabling investors to make informed decisions on buying or selling stocks to ...

This paper explores effective methods for predicting gold prices, proposing three modeling strategies: a standalone Long Short-Term Memory (LSTM) network, a Convolutional Self-Attention (CSA) Network, ...

This software is provided for educational and research purposes only. It is NOT financial advice and should NOT be used for actual trading without: Proper financial licenses and regulatory compliance ...

In the context of global energy shortages, traditional energy sources face issues of limited reserves and high prices. As a result, the importance of energy storage technology is increasingly ...

Tesla dropped its long-awaited more affordable models on Tuesday. The Model 3 Standard and Model Y Standard cost less, but come with some compromises. Tesla eliminated FM/AM radio from the ...

With the widespread application of lithium-ion batteries in electric vehicles and energy storage systems, health monitoring and remaining useful life prediction have become critical components of ...

Landslides are one of the most prevalent natural geological disasters, causing significant economic losses, damaging public environments, and posing severe threats to human lives. Landslide ...

This study proposes a hybrid modeling approach that integrates a Physics Informed Neural Network (PINN) and a long short-term memory (LSTM) network to predict river water temperature in a defined ...