Titlebook: Geomorphic Risk Reduction Using Geospatial Methods and Tools; Raju Sarkar,Sunil Saha,Rajib Shaw Book 2024 The Editor(s) (if applicable) an

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預(yù)測(cè)

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一夫一妻制

https://doi.org/10.1007/978-981-99-7707-9Geomorphic hazard; Machine learning technique; Satellite image; Resilience process; Risk reduction techn

Cosmopolitan

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2196-4106 rent geomorphic hazards risk.Applies advanced machine learniThis book explores the use of advanced geospatial techniques in geomorphic hazards modelling and risk reduction. It also compares the accuracy of traditional statistical methods and advanced machine learning methods and addresses the differ

頭腦冷靜

Metallic Waveguides and Resonant Cavities,RMSE and the greatest ROC-AUC (0.867) and kappa index (0.884) during the validation phase (0.234). The anticipated model is reliable for minimizing the impact of landslides in the research region and planning land development.

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Electromagnetic waves in conductors, were used to prepare the flood susceptibility maps. The models used were J48DT, J48DT-AdaBoost, and J48DT-Bagging. Finally, the outputs obtained were validated using six techniques namely, Sensitivity, Specificity, AUC (%), Kappa, MAE, and RMSE.

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