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Artur is a copywriter and SEO specialist, as well as a small business owner. In his free time, he loves to play computer games and is glad that he was able to connect his professional career with his ...

Predicts velocity and pressure fields for various Reynolds numbers. Integrates CAE for dimensionality reduction and reconstruction. Uses LSTM to capture temporal dynamics for short-term predictions.

A new machine learning approach that draws inspiration from the way the human brain seems to model and learn about the world has proven capable of mastering a number of simple video games with ...

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 ...

Long short-term memory (LSTM) networks have become indispensable tools in hydrological modeling due to their ability to capture long-term dependencies, handle non-linear relationships, and integrate ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Liquefied Petroleum Gas (LPG) is a crucial energy source, widely utilized in ...

These systems collect huge amounts of patient information, including diagnosis codes representing temporal medical history. Sequential diagnostic information has proven valuable for predicting patient ...

Abstract: Malicious website protection through malware URL detection is very important for cybersecurity. This paper discusses the use of deep learning algorithms in detecting malware URLs by ...

1 Department of Computer Engineering, College of Engineering and Petroleum, Kuwait University, Safat, Kuwait 2 Department of Computer Sciences, University of Hamburg, Hamburg, Germany The metrical ...