Tag: CNN-LSTM

A two-stage framework that corrects coarse weather forecasts before predicting solar output halved day-ahead power forecast errors at a 20 ...

A lightweight CNN-LSTM framework classifies negative, neutral, and positive sentiment from live video at 84.89 percent accuracy on RAVDESS, outperforming ...

A new training framework called GLIMMER improves blood glucose forecasting in type 1 diabetes by penalizing errors in dangerous glucose ...

A systematic comparison of twelve bias correction methods for CMIP6 models in Jiangsu Province, China, shows that machine learning approaches ...

A deployment-efficient CNN-LSTM framework with channel attention detects encrypted, imbalanced, and heterogeneous malicious traffic in real time on CPU-only hardware, ...

Researchers in northeastern Brazil combined a CNN–LSTM deep-learning architecture with decades of Landsat imagery to forecast MNDWI-derived coastal states in ...

Malaysian researchers have built a hybrid CNN-LSTM traffic forecasting system that pairs deep learning accuracy with Formal Concept Analysis to ...

A new hybrid WOA-EEMD-CNN-LSTM framework uses whale-inspired optimization and deep learning to predict dissolved oxygen with high accuracy in noisy, ...

Researchers have developed VoteChain, a voting-based blockchain consensus framework that embeds a lightweight CNN-LSTM anomaly detector to cut energy use ...

A new study combines mass spectrometry, infrared spectroscopy, and deep learning to identify the exact taste and aroma compounds that ...