Publication:

Leak localization in water distribution networks by directly fitting the learning parameters of a Gaussian naive Bayes classifier

Date

2022
Proceedings Paper
Simple item page Full metadata Statistics
 
dc.contributor.authorMazaev, G.
dc.contributor.authorWeyns, Michael
dc.contributor.authorVancoillie, F.
dc.contributor.authorVaes, G.
dc.contributor.authorOngenae, Femke
dc.contributor.authorVan Hoecke, Sofie
dc.contributor.imecauthorWeyns, Michael
dc.contributor.imecauthorOngenae, Femke
dc.contributor.imecauthorVan Hoecke, Sofie
dc.contributor.orcidimecWeyns, Michael::0000-0002-6157-5997
dc.contributor.orcidimecVan Hoecke, Sofie::0000-0002-7865-6793
dc.contributor.orcidimecOngenae, Femke::0000-0003-2529-5477
dc.date.accessioned2024-02-02T11:18:48Z
dc.date.available2023-01-20T10:55:20Z
dc.date.available2024-02-02T11:18:48Z
dc.date.embargo2022-12-20
dc.date.issued2022
dc.identifier.issn/
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/41000
dc.source.beginpage4854
dc.source.conferenceBig Data2022, the IEEE International Conference on Big Data
dc.source.conferencedate17-20/12/2022
dc.source.conferencelocationOsaka, Japan
dc.source.endpage4859
dc.source.journal/
dc.source.numberofpages6
dc.title

Leak localization in water distribution networks by directly fitting the learning parameters of a Gaussian naive Bayes classifier

dc.typeProceedings paper
dspace.entity.typePublication
Files

Original bundle

Name:
DS597.pdf
Size:
9.76 MB
Format:
Unknown data format
Description:
Accepted version
Download
Name:
Leak_localization_in_Water_Distribution_Networks_By_Directly_Fitting_the_Learning_Parameters_of_a_Gaussian_Naive_Bayes_Classifier.pdf
Size:
2.39 MB
Format:
Adobe Portable Document Format
Description:
Published version
Download
Publication available in collections:
Conference contributions