American Institute of Physics

Modeling drifting seaweed rafts that clog ports and beaches

Machine learning and other modeling approaches could aid in forecasting the arrival of floating Sargassum rafts that clog ...
Game Rant

These Tutorials Are So Long, They Hurt Their Games

Ritwik is a passionate gamer who has a soft spot for JRPGs. He's been writing about all things gaming for six years and counting. No matter how great a title's gameplay may be, there's always the ...
Hosted on MSN

LSTM Neural Networks Finally Explained — No More Confusion!

LSTM Recurrent Neural Network is a special version of the RNN model. It stands for Long Short-Term Memory. The simple RNN has a problem that it cannot remember the context in a long sentence because ...
IEEE

Data-Driven Optimized Load Forecasting: An LSTM-Based RNN Approach for Smart Grids

Abstract: Accurate load forecasting is essential for ensuring the stability and efficiency of modern power systems, particularly in the context of increasing renewable energy integration. This study ...
Scientific Research Publishing

Sherstinsky, A. (2020). Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network. Physica D: Nonlinear Phenomena, 404, Article 132306.

ABSTRACT: Accurate precipitation forecasting is crucial for mitigating the impacts of extreme weather events and enhancing disaster preparedness. This study evaluates the performance of Long ...
Scientific Research Publishing

Waqas, M., & Humphries, U. W. (2024). A Critical Review of RNN and LSTM Variants in Hydrological Time Series Predictions. MethodsX, 13, 102946.

ABSTRACT: Accurate precipitation forecasting is crucial for mitigating the impacts of extreme weather events and enhancing disaster preparedness. This study evaluates the performance of Long ...