Herrera Fernández, AM.; Izquierdo Sebastián, J.; Pérez García, R.; Montalvo Arango, I. (2012). Multi-Agent Adaptive Boosting on Semi-Supervised Water Supply Clusters. ADVANCES IN ENGINEERING SOFTWARE. 50:131-136. https://doi.org/10.1016/j.advengsoft.2012.02.005
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/30406
Title:
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Multi-Agent Adaptive Boosting on Semi-Supervised Water Supply Clusters
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Author:
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Herrera Fernández, Antonio Manuel
Izquierdo Sebastián, Joaquín
Pérez García, Rafael
Montalvo Arango, Idel
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UPV Unit:
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Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient
Universitat Politècnica de València. Instituto Universitario de Matemática Multidisciplinar - Institut Universitari de Matemàtica Multidisciplinària
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Issued date:
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Abstract:
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[EN] The division of a water supply network (WSN) into isolated supply clusters aims at improving the management
of the whole system. This paper deals with the application of spectral clustering to achieve this
aim. A ...[+]
[EN] The division of a water supply network (WSN) into isolated supply clusters aims at improving the management
of the whole system. This paper deals with the application of spectral clustering to achieve this
aim. A semi-supervised approach can take into account the graph structure of a network and incorporate
the corresponding hydraulic constraints and the other available vector information from the WSN. Several
of the disadvantages of these methodologies stem from the largeness of the most WSN and the associated
computational complexity. To solve these problems, we propose subsampling graph data to run
successive weak clusters and build a single robust cluster configuration. The resulting methodology
has been tested in a real network and can be used to successfully partition large WSNs.
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Subjects:
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Clustering
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Graph theory
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Sampling
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Semi-supervised learning
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Multi-agent systems
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Water supply networks
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Copyrigths:
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Cerrado |
Source:
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ADVANCES IN ENGINEERING SOFTWARE. (issn:
0965-9978
)
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DOI:
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10.1016/j.advengsoft.2012.02.005
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Publisher:
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ELSEVIER SCI LTD
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Publisher version:
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http://dx.doi.org/10.1016/j.advengsoft.2012.02.005
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Project ID:
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info:eu-repo/grantAgreement/MICINN//DPI2009-11591/ES/Aplicacion De Herramientas Del Analisis Inteligente De Datos En La Gestion Tecnica De Sistemas De Distribucion Y Evacuacion De Aguas/ /
info:eu-repo/grantAgreement/GVA//ACOMP%2F2011%2F188/
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Thanks:
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This work has been performed with the support of project IDA-WAS, DPI2009-11591 from the Direccion General de Investigacion del Ministerio de Educacion y Ciencia (Spain) and ACOMP/2011/188 from the Conselleria de Educacio ...[+]
This work has been performed with the support of project IDA-WAS, DPI2009-11591 from the Direccion General de Investigacion del Ministerio de Educacion y Ciencia (Spain) and ACOMP/2011/188 from the Conselleria de Educacio of the Generalitat Valenciana. The use of English in this paper was revised by John Rawlins.
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Type:
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Artículo
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