[HTML][HTML] Advanced hybrid CNN-Bi-LSTM model augmented with GA and FFO for enhanced cyclone intensity forecasting
Predicting cyclone intensity is an important aspect of weather forecasting since it influences
disaster preparation and response. This framework addresses the pressing need for precise …
disaster preparation and response. This framework addresses the pressing need for precise …
Bridging satellite missions: deep transfer learning for enhanced tropical cyclone intensity estimation
Geostationary satellites are valuable tools for monitoring the entire lifetime of tropical
cyclones (TCs). Although the most widely used method for TC intensity estimation is manual …
cyclones (TCs). Although the most widely used method for TC intensity estimation is manual …
Deep Learning and Wavelet Transform Combined with Multi-channel Satellite Images for Tropical Cyclone Intensity Estimation
CJ Zhang, MS Chen, LM Ma… - IEEE Journal of Selected …, 2025 - ieeexplore.ieee.org
Tropical cyclone (TC) is a highly catastrophic weather event, and accurate estimation of
intensity is of great significance. The current proposed TC intensity estimation model focuses …
intensity is of great significance. The current proposed TC intensity estimation model focuses …
Elevated surface ozone concentration caused by subtropical cyclones and topographical effect: Model simulation and field measurement
This study pioneered the forecasting of typhoon trajectories and conducted the
comprehensive analysis of pre-typhoon surface O 3 patterns using WRF-Chem model …
comprehensive analysis of pre-typhoon surface O 3 patterns using WRF-Chem model …
Unbiased High-Precision Cloud Detection for Advanced Himawari Imager using Automatic Machine Learning
Clouds play a pivotal role in the global radiation budget and energy cycle, making accurate
cloud detection via satellite remote sensing essential for understanding their evolutions …
cloud detection via satellite remote sensing essential for understanding their evolutions …
Tropical cyclone intensity estimation through convolutional neural network transfer learning using two geostationary satellite datasets
Accurate prediction and monitoring of tropical cyclone (TC) intensity are crucial for saving
lives, mitigating damages, and improving disaster response measures. In this study, we …
lives, mitigating damages, and improving disaster response measures. In this study, we …
Improved forecasting of extreme hurricane events by integrating spatio-temporal CNN-RF learning of tropical cyclone characteristics
Assessing hurricane predictions in a changing climate is one of the most challenging
weather forecast problems today. Furthermore, effectively integrating information-rich …
weather forecast problems today. Furthermore, effectively integrating information-rich …
The Classification of Tropical Storm Systems in Infrared Geostationary Weather Satellite Images Using Transfer Learning
J Senior-Williams, F Hogervorst… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
The work performed in this study evaluated the application of generalized pretrained object
detection models for the identification and classification of tropical storm (TS) systems …
detection models for the identification and classification of tropical storm (TS) systems …