| dc.contributor.author |
Mata, J.
|
pt_BR |
| dc.date.accessioned |
2022-04-01T10:20:54Z |
pt_BR |
| dc.date.accessioned |
2022-04-08T09:05:44Z |
|
| dc.date.available |
2022-04-01T10:20:54Z |
pt_BR |
| dc.date.available |
2022-04-08T09:05:44Z |
|
| dc.date.issued |
2017-07 |
pt_BR |
| dc.identifier.uri |
https://repositorio.lnec.pt/jspui/handle/123456789/1014789 |
|
| dc.description.abstract |
To show how quality control of data, statistics, Machine Learning, and Artificial Intelligence will
change Infrastructure Safety and Risk Management and Public Safety Forever is expected with
the RESTATE project. This work aims to develop methodologies and procedures to support
decision-making for the timely safety control of large infrastructures under operating
conditions. This project aims to address new methodologies based on Deep Learning to create
value in three main activities: quality control of monitoring data, analysis and interpretation of
the structural behaviour, and safety assessment. |
pt_BR |
| dc.language.iso |
eng |
pt_BR |
| dc.publisher |
University of Deusto Rovira i Virgili University |
pt_BR |
| dc.rights |
openAccess |
pt_BR |
| dc.subject |
Concrete dam |
pt_BR |
| dc.subject |
Decision support system |
pt_BR |
| dc.subject |
Machine Learning |
pt_BR |
| dc.title |
RESTATE Project: Real-time decision support system for safety assessment of large concrete dams. The action cycle: Data-Information-Knowledge-Decision Making |
pt_BR |
| dc.type |
conferenceObject |
pt_BR |
| dc.description.pages |
1 |
pt_BR |
| dc.identifier.local |
Bilbao, Spain |
pt_BR |
| dc.description.sector |
DBB/NO |
pt_BR |
| dc.identifier.conftitle |
nternational Summer School on Deep Learning 2017 |
pt_BR |
| dc.contributor.peer-reviewed |
SIM |
pt_BR |
| dc.contributor.academicresearchers |
NAO |
pt_BR |
| dc.contributor.arquivo |
SIM |
pt_BR |