Characterization of Water Consumers in Urban Areas Using Artificial Intelligence and Data Analysis

UDC.coleccionPublicacións UDCes_ES
UDC.endPage160es_ES
UDC.startPage153es_ES
dc.contributor.authorRubiños, Manuel
dc.contributor.authorÁlvarez-Crespo, Marta María
dc.contributor.authorZayas-Gato, Francisco
dc.contributor.authorCalvo-Rolle, José Luis
dc.date.accessioned2025-01-20T19:22:17Z
dc.date.available2025-01-20T19:22:17Z
dc.date.issued2024
dc.description.abstractThis work presents the first steps of the integration of AI techniques in the field of urban water management, more precisely in the line of urban consumption forecasting and user characterization. For this purpose, different data visualization and clustering techniques are applied and the results are compared, in order to study which ones are more suitable for pattern extraction and detection. The resulting user profiles are then contrasted to determine common characteristics among the same group members and differences among others. Average daily consumption and variability are proposed as the variables on which the characterization is based.es_ES
dc.identifier.urihttp://hdl.handle.net/2183/40799
dc.language.isoenges_ES
dc.relation.urihttps://doi.org/10.17979/spudc.9788497498913.22
dc.rightsAtribución 4.0es_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectData sciencees_ES
dc.subjectData visualizationes_ES
dc.subjectUser characterizationes_ES
dc.subjectWater consumptiones_ES
dc.subjectUrban water managementes_ES
dc.subjectArtificial Intelligencees_ES
dc.subjectClustering
dc.titleCharacterization of Water Consumers in Urban Areas Using Artificial Intelligence and Data Analysises_ES
dc.typeconference outputes_ES
dspace.entity.typePublication
relation.isAuthorOfPublication1dc63c83-160d-404b-b135-da7d537b3a7f
relation.isAuthorOfPublicationa345ef5f-23ed-453f-821c-1cc377f87c6f
relation.isAuthorOfPublication98607887-2bb4-45e1-9963-2bc8e7da9cd0
relation.isAuthorOfPublication89839e9c-9a8a-4d27-beb7-476cfab8965e
relation.isAuthorOfPublication.latestForDiscovery1dc63c83-160d-404b-b135-da7d537b3a7f

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
XoveTIC_2024_proceedings_Parte22.pdf
Size:
456.78 KB
Format:
Adobe Portable Document Format
Description: