Analysis of sea water infiltration in a sewage treatment plant using Random Forests and variable importance measures

Abstract

In ltration of salt water in water-treatment plants is a current challenge in Spanish coasts. This is a problem because when the sea water enters into the plant, it damages the lters and compromise the quality of the water ltration. In order to detect this water in ltration, the usual approach is to measure conductivity of the ows (ability to conduct electricity). The work subsequently described in this document is a project funded by a research internship of the Universitat Jaume I's C atedra FACSA de Innovaci on del Ciclo Integral del Agua. The goal of this project is to detect when a saltwater in ltration has occurred and to detect the most relevant variables which are related with the rising of water conductivity. The approach chosen to deal with this problem has been the technique of Random Forests, a family of algorithm based on decision trees. The reasons of this elections are mainly the exibility with respect missing data that Random Forests allow; the \black box"-like behaviour that does not need an a priori knowledge of the data structure; and the ability to explore the variables' importance through several measures. In this project the mentioned methodology will be explained in detail, as well as the results obtained and the conclusions that follows them.