Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA) |
| Untertitel | October 20-21, 2015, Rabat, Morocco, ENSIAS, Rabat, Morocco |
| Erscheinungsort | Piscataway, NJ |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| Seiten | 1838-1843 |
| Seitenumfang | 6 |
| ISBN (elektronisch) | 9781479975600 |
| Publikationsstatus | Veröffentlicht - 2015 |
| Extern publiziert | Ja |
| Veranstaltung | Symposium on Computational Intelligence for Engineering Solutions (CIES) at the IEEE Symposium Series on Computational Intelligence (SSCI) - Capr Town, Cape Town, Südafrika Dauer: 7 Dez. 2015 → 10 Dez. 2015 |
Abstract
This work aims to scrutinise a proprietary dataset containing major accidents occurred in high-Technology facilities, in order to disclose relevant features and indicate a path to the recognition of the genesis of human errors. The application of a tailored Hierarchical Agglomerative Clustering method will provide means to understand data and identify key similarities among accidents and significant interfaces between human factors, the organisational environment and the technology. Conclusions to improve the human performance based on the clustering results are then discussed.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Artificial intelligence
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2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA): October 20-21, 2015, Rabat, Morocco, ENSIAS, Rabat, Morocco. Piscataway, NJ: Institute of Electrical and Electronics Engineers Inc., 2015. S. 1838-1843.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - A clustering approach to a major-accident data set
T2 - Symposium on Computational Intelligence for Engineering Solutions (CIES) at the IEEE Symposium Series on Computational Intelligence (SSCI)
AU - Moura, Raphael
AU - Beer, Michael
AU - Doell, Christoph
AU - Kruse, Rudolf
PY - 2015
Y1 - 2015
N2 - This work aims to scrutinise a proprietary dataset containing major accidents occurred in high-Technology facilities, in order to disclose relevant features and indicate a path to the recognition of the genesis of human errors. The application of a tailored Hierarchical Agglomerative Clustering method will provide means to understand data and identify key similarities among accidents and significant interfaces between human factors, the organisational environment and the technology. Conclusions to improve the human performance based on the clustering results are then discussed.
AB - This work aims to scrutinise a proprietary dataset containing major accidents occurred in high-Technology facilities, in order to disclose relevant features and indicate a path to the recognition of the genesis of human errors. The application of a tailored Hierarchical Agglomerative Clustering method will provide means to understand data and identify key similarities among accidents and significant interfaces between human factors, the organisational environment and the technology. Conclusions to improve the human performance based on the clustering results are then discussed.
UR - http://www.scopus.com/inward/record.url?scp=84964961797&partnerID=8YFLogxK
U2 - 10.1109/SSCI.2015.256
DO - 10.1109/SSCI.2015.256
M3 - Conference contribution
AN - SCOPUS:84964961797
SP - 1838
EP - 1843
BT - 2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA)
PB - Institute of Electrical and Electronics Engineers Inc.
CY - Piscataway, NJ
Y2 - 7 December 2015 through 10 December 2015
ER -