IEEE

Development of a Long Short-Term Memory (LSTM)-Based Statistical Model for Earthquake Forecasting in Central Asia

Abstract: Earthquake forecasting using traditional methods remains a complex task due to the inherent nonlinearity and stochastic nature of seismic activity. Therefore, this study examines the ...
Frontiers

A Hybrid CNN-LSTM approach for multi-step discharge forecasting with satellite data

The final, formatted version of the article will be published soon. An innovative hybrid forecasting model was developed to predict hourly river discharges up to 24 hours in advance. The proposed ...
IEEE

Evaluating LSTM Performance Across Varying Historical Data Sequences for Weather Forecasting in Virtual Power Plant Optimization

Abstract: The operation of Virtual Power Plants (VPPs), integrating renewable sources like wind and solar, relies on accurate weather forecasting. Long Short-Term Memory (LSTM) networks are widely ...