Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/128087
Title: Técnicas de aprendizaje automático para el análisis de la salinidad de aguas en el valle del Guadalhorce
Author: Alonso Cabrera, Carlos Alberto
Director: Casas-Roma, Jordi  
Tutor: Sanchez-Bocanegra, Carlos Luis  
Abstract: The Junta de Andalucía is in charge of managing and operating three dams (Conde de Guadalhorce, Guadalhorce and Guadalteba Dam) that act on the Guadalhorce River, and its Guadalteba and Turón tributaries. There are data collected on these dams since 1974. The main need for the work arises from the concern of the Junta de Andalucía to know what the data collected shows, and in particular, the data on the salinity of Guadalhorce dam and how it influences in the rest of the dams. At present, the water from the three dams is mixed, according to their capacity, to obtain water for consumption, irrigation, livestock, etc. The aim is to apply Machine Learning methods to know what parameters influence the mixture salinity and what is the optimal mixture of the three dams in order to skew water for consumption, irrigation and livestock. Use the least amount of fresh water, province of Guadalteba and Conde de Guadalhorce, so that the mixture is usable. How parameters, such as height, rain, etc., influence the salinity of the water in the Guadalhorce dam. Relate the salinity of the Guadalhorce dam to the salinity obtained from the mixture. The data provided by the Junta de Andalucía, which collect different information on the dams, will be pre-processed, analyzed and displayed to extract a detailed analysis.
Keywords: salinity
data analysis
dam
Document type: info:eu-repo/semantics/masterThesis
Issue Date: Jan-2021
Publication license: http://creativecommons.org/licenses/by-nc-nd/3.0/es/  
Appears in Collections:Bachelor thesis, research projects, etc.

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