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http://hdl.handle.net/10609/63587
Title: Ús d'algorismes d'aprenentatge automàtic en entorns big data per a l'obtenció de models predictius de contaminació
Author: Bonet Vilela, Fidel
Director: Isern Alarcón, David
Tutor: Ventura Royo, Carles  
Others: Universitat Oberta de Catalunya
Keywords: machine learning
big data
Apache Hadoop
Issue Date: 1-Jun-2017
Publisher: Universitat Oberta de Catalunya
Abstract: The goal of this project is the use of machine learning algorithms in big data environments for obtaining predictive models of air pollution. Based on historical weather, traffic and air pollution datasets from sensors distributed throughout the territory, several machine learning models have been obtained. These models have been created in a big data environment because, nowadays, the amount of data collected by sensors is very large. In order to accomplish this, firstly, Apache Hadoop clusters have been implemented in two architectures: a pseudo-distributed one, using a virtual machine, and a distributed one in the Amazon Web Services platform. Afterwards, Apache Hive has been used to load the data into an HDFS distributed file system and preprocess it. Finally, Apache Mahout has been used as a machine learning library.
Language: Catalan
URI: http://hdl.handle.net/10609/63587
Appears in Collections:Bachelor thesis, research projects, etc.

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fbonetviTFG0617memòria.pdfMemòria del treball fi de grau12.26 MBAdobe PDFView/Open
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