par Ramos-Martínez, Eva;Gutiérrez-Pérez, Joanna J.A.;Izquierdo, Joaquín;Pérez-García, Rafael;Herrera, Manuel 
Référence Frontiers in artificial intelligence and applications, 256, page (307-310)
Publication Publié, 2013
Référence Frontiers in artificial intelligence and applications, 256, page (307-310)
Publication Publié, 2013
Article révisé par les pairs
| Résumé : | Biofilm is formed by complex communities of microorganisms that grow within a drinking water distribution system (DWDS) and can lead to various undesirable problems. Nowadays, biofilm represents a paradigm in the management of all DWDSs. In this context, we focus on how the physical and hydraulics characteristics of DWDSs affect the development of these communities of microorganisms, looking for the problematic points associated with biofilm development within a DWDS. Various studies have been performed in relation to the influence that a number of characteristics of DWDSs have on biofilm development. Nevertheless, their joint influence, apart from few exceptions, has been scarcely studied, due to the complexity of the community and the environment under study. To achieve this goal we have compiled biofilm data from different sources and pre-processed it, applying some machine learning methods, to get a complete and extensive enough database to perform inference by posterior analysis. In this case, an agent-based label negotiation technique is applied to the obtained database to identify important pre-relationships between the physical and the hydraulic characteristics of the pipes, their specific location, and biofilm development in a given DWDS. © 2013 The authors and IOS Press. All rights reserved. |
