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dc.contributorBelanche Muñoz, Luis Antonio
dc.contributor.authorSánchez-Mendoza, David
dc.date.accessioned2012-09-21T12:42:22Z
dc.date.available2012-09-21T12:42:22Z
dc.date.issued2012-06-20
dc.identifier.urihttp://hdl.handle.net/2099.1/16066
dc.description.abstractThe Microbial Source Tracking problem (MST) has to do with the determination of the fecal pollution origin in waters by the use of microbial and chemical indicators. This document introduces a methodology for solving MST problem from the machine learning point of view reporting both the arising specifi c problems and challenges and how they have been addressed. The simplest instance of the MST problem has already been solved to satisfaction using machine learning techniques on recently and heavily polluted waters, however, our methodology accepts examples showing di fferent concentration levels and using indicators (variables) with diff erent environmental persistence. The theoretical methodology is supported by a software which implements it and has been validated using two real datasets with real data from diff erent geographical and climatic areas.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
dc.subjectÀrees temàtiques de la UPC::Desenvolupament humà i sostenible::Desenvolupament humà::Aigua i sanejament
dc.subject.lcshMachine learning
dc.subject.lcshWater pollution
dc.subject.lcshSewage - Microbiology
dc.titleA Software system for the microbial source tracking problem
dc.typeMaster thesis
dc.subject.lemacAprenentatge automàtic
dc.subject.lemacAigua--Contaminació
dc.subject.lemacAigües residuals--Microbiologia
dc.rights.accessOpen Access
dc.audience.educationlevelMàster
dc.audience.mediatorFacultat d'Informàtica de Barcelona
dc.audience.degreeMÀSTER UNIVERSITARI EN INTEL·LIGÈNCIA ARTIFICIAL (Pla 2009)


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