Flood susceptibility mapping using an Artificial Neural Network model: the case study of Southern Italy

Michele Del Vecchio; Filippo Balestra; Maria Antonia Pedone; Dina Pirone; Danilo Spina; Salvatore Manfreda; Giovanni Menduni

doi:https://doi.org/10.5194/egusphere-egu22-12328

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EGU22-12328

https://doi.org/10.5194/egusphere-egu22-12328

EGU General Assembly 2022

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Flood susceptibility mapping using an Artificial Neural Network model: the case study of Southern Italy

Michele Del Vecchio¹, Filippo Balestra¹, Maria Antonia Pedone³, Dina Pirone², Danilo Spina³, Salvatore Manfreda², and Giovanni Menduni¹

Michele Del Vecchio et al.

¹Politecnico di Milano, Department of Civil and Environmental Engineering, Milano, Italy
²Department of Civil, Environmental and Architectural Engineering, Università degli Studi di Napoli Federico II, Napoli, 80125, Italy
³Fondazione Politecnico di Milano, Milano, 20133, Italy

How to cite: Del Vecchio, M., Balestra, F., Pedone, M. A., Pirone, D., Spina, D., Manfreda, S., and Menduni, G.: Flood susceptibility mapping using an Artificial Neural Network model: the case study of Southern Italy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12328, https://doi.org/10.5194/egusphere-egu22-12328, 2022.

This abstract has been withdrawn on 24 May 2022.