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Deep Learning for Wildfire Risk Prediction by mustafasilsupur125 is a document available to read on EtoBox.
This study presents a deep learning model for predicting wildfire risk in eastern China by integrating multi-source datasets, including satellite data and human activity indicators. The model employs ConvLSTM with attention mechanisms to enhance prediction accuracy, achieving improvements in key metrics such as accuracy and Kappa coefficient. Results indicate that structural features significantly influence wildfire risk, suggesting the need for their consideration in future predictive models.
- Author
- mustafasilsupur125
- Language
- EN