Presentation Open Access
Anomaly detection in nuclear reactors using deep learning
Francesco Caliva
Citation Style Language JSON Export
{
"publisher": "Zenodo",
"DOI": "10.5281/zenodo.4314941",
"language": "eng",
"title": "Anomaly detection in nuclear reactors using deep learning",
"issued": {
"date-parts": [
[
2020,
12,
8
]
]
},
"abstract": "<p>Monitoring nuclear reactors working at nominal conditions is fundamental for safety purposes.</p>",
"author": [
{
"family": "Francesco Caliva"
}
],
"id": "4314941",
"event-place": "Remote meeting",
"type": "speech",
"event": "IAEA Consultancy Meeting on Machine Learning for Nuclear Data"
}
15
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downloads
| All versions | This version | |
|---|---|---|
| Views | 15 | 15 |
| Downloads | 8 | 8 |
| Data volume | 138.6 MB | 138.6 MB |
| Unique views | 12 | 12 |
| Unique downloads | 8 | 8 |
Indexed in
- Publication date:
- December 8, 2020
- DOI:
-
- Grants:
-
European Commission:
- CORTEX - Core monitoring techniques and experimental validation and demonstration (754316)
- Meeting:
- IAEA Consultancy Meeting on Machine Learning for Nuclear Data, Remote meeting, December 8-11, 2020
- License (for files):
- Creative Commons Attribution 4.0 International