A new approach based on Balancing Composite Motion Optimization and Deep Neural Networks for spatial prediction of landslides at tropical cyclone areas

Landslides are a significant geological hazard that annually cause extensive damage and loss of life worldwide. Therefore, it is crucial to have reliable prediction models for landslide susceptibility in order to identify high-risk areas and implement proactive measures to prevent or mitigate their...

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Veröffentlicht in:	IEEE access 2023-01, Vol.11, p.1-1
Hauptverfasser:	Tuan, Tran Anh, Pha, Phan Dong, Tam, Tran Thi, Bui, Dieu Tien
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Balancing Balancing composite motion Benchmarks Biological system modeling Cyclones Decision making Deep learning Deep neural network Geographic information systems Geological hazards GIS Land use Landslide Landslides Landslides & mudslides Machine learning Neural networks Optimization Performance evaluation Performance prediction Prediction algorithms Prediction models Predictive models Rainfall Support vector machines Tropical cyclones Vietnam
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