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Spatiotemporal Forest Cover Prediction Model by gdrivebuatfilm is a document available to read on EtoBox.

What is Spatiotemporal Forest Cover Prediction Model about?

The document presents a novel hybrid model, ResConvLSTM-Att, for spatiotemporal forest cover prediction, integrating residual neural networks, ConvLSTM networks, and attention mechanisms. This model outperformed existing deep learning models in accuracy, achieving a root mean square error (RMSE) of 6.9% and a coefficient of determination of 0.965 in Tasmania, Australia. The study highlights the importance of explanatory variables in forest cover dynamics and demonstrates the model

Author

gdrivebuatfilm

Language

EN