2026-04-17T22:52:24Zhttps://recercat.cat/oai/request

oai:recercat.cat:2099.1/160662025-07-23T04:35:20Zcom_2072_1033col_2072_452951

00925njm 22002777a 4500 dc Sánchez-Mendoza, David author 2012-06-20 The 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. Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Desenvolupament humà::Aigua i sanejament Machine learning Water pollution Sewage - Microbiology Aprenentatge automàtic Aigua--Contaminació Aigües residuals--Microbiologia A Software system for the microbial source tracking problem