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 ...

Abstract: This study combines the Long Short-Term Memory (LSTM) network with Local Interpretable Model-agnostic Explanation (LIME) to enhance both predictive accuracy and interpretability in financial ...

Abstract: Long Short-Term Memory (LSTM) networks are particularly useful in recommender systems since user preferences change over time. Unlike traditional recommender models which assume static ...

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 ...

I've been trying to train a simple LSTM model in mlpack for a many-to-one prediction task — basically, it takes 50 points from a sine function and predicts the next one. But the model just doesn't ...

A long-elusive “theory of everything,” also known as a unified field theory, may finally be within reach as Finnish researchers at Aalto University unveil a new quantum theory of gravity that is ...

Black Holes Scientists use Stephen Hawking theory to propose 'black hole morsels' — strange, compact objects that could reveal new physics Black Holes Astronomers simulate a star's final moments as it ...

本项目基于PyTorch实现了长短期记忆网络（LSTM），用于预测城轨线网15分钟粒度的客运量数据。 📂 项目结构 . ├── lstm.py # 主程序，包含数据读取、模型训练与预测 ├── lstm_model.pth # 保存的模型参数文件 ├── LSTM.png # 模型预测结果可视化图 └── README.md ...

The wind energy industry is witnessing a new era of extraordinary growth as the demand for renewable energy continues to grow. However, accurately predicting wind speed remains a significant challenge ...