Marco Martino Rosso
Biographic Data
| ID | 9960836 |
|---|---|
| NAME | Marco Martino Rosso |
| GIVEN NAMES | Marco Martino |
| FAMILY NAME | Rosso |
| SIGNATURE | ROSSO M M |
| AFFILIATIONS | Politecnico di Torino |
| ORCID | 0000-0002-9098-4132 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Machine learning model for predicting post-earthquake reconstruction grants of masonry buildings from seismic vulnerability features
In the aftermath of the 2009 L’Aquila earthquake in Italy, public authorities established a procedure to determine reconstruction grants for buildings on the basis of evidence from visual inspections, as documented in a dedicated form (i.e., the AeDES form). The calculation is driven by two main aspects, namely the observed damage and the assessed vulnerability level. For masonry buildings, which account for more than 90% of structures in small u…
Damage classification after the 2009 L’Aquila earthquake using multinomial logistic regression and neural networks
Post-earthquake surveys represent a fundamental tool for managing the emergency phase after a strong earthquake. In Italy, the evaluation of the post-earthquake functionality of ordinary buildings is based on the AeDES forms (Agibilitá e Danno nell’Emergenza Sismica, or equivalently, Rapid Post-Earthquake Damage evaluation forms). This form includes information on the building and records of the observed damage classified according to type and in…
No prominent works on this page.
Damage classification after the 2009 L’Aquila earthquake using multinomial logistic regression and neural networks
Post-earthquake surveys represent a fundamental tool for managing the emergency phase after a strong earthquake. In Italy, the evaluation of the post-earthquake functionality of ordinary buildings is based on the AeDES forms (Agibilitá e Danno nell’Emergenza Sismica, or equivalently, Rapid Post-Earthquake Damage evaluation forms). This form includes information on the building and records of the observed damage classified according to type and in…
Machine learning model for predicting post-earthquake reconstruction grants of masonry buildings from seismic vulnerability features
In the aftermath of the 2009 L’Aquila earthquake in Italy, public authorities established a procedure to determine reconstruction grants for buildings on the basis of evidence from visual inspections, as documented in a dedicated form (i.e., the AeDES form). The calculation is driven by two main aspects, namely the observed damage and the assessed vulnerability level. For masonry buildings, which account for more than 90% of structures in small u…
Seismic Performance and Analysis (2 works) · Artificial Intelligence (1 work) · Artificial neural network (1 work) · Civil and Structural Engineering Research (1 work) · Computer Science (1 work) · Earthquake Detection and Analysis (1 work) · Emergency response (1 work) · Engineering (1 work) · Forensic engineering (1 work) · Geology (1 work)