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Title: Predicción de la calidad del aire de Madrid mediante modelos supervisados
Author: Villalba Pintado, Gabriel
Director: Casas Roma, Jordi
Tutor: Parada Medina, Raúl
Keywords: air quality index
data mining
prediction
open data
Issue Date: 9-Jun-2019
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: Each day, a person breathes on average an air volume of 12,000 liters (12 m³). In cities, the quality of that air is usually not very good. It can be contaminated by traffic, industry and many other activities. We know that there is a direct relationship between the quality of the air we breathe and human health, therefore, the city of Madrid has a plan for air quality and climate change. This plan tries to guarantee the air quality of the city and defines a series of actions to reduce pollution, such as traffic restrictions. These actions are taken based on measurements throughout the city and unfortunately are usually taken with little anticipation. The objective of this master's degree final project is to use different data mining algorithms to create a model that allows us to make a prediction of the quality of the air in Madrid in a precise manner and with greater anticipation. For this purpose, it will be used open data with a historic of air quality, meteorology and the city's work calendar. These data will be combined and prepared to be used with different techniques and data mining algorithms (MLP, LSTM, CNN and SVM). From the generated models, it will be verified if it is possible to make a prediction of the air quality in Madrid with great precision and anticipation in order to improve the current planning of established actions and restrictions.
Language: Spanish
URI: http://hdl.handle.net/10609/99446
Appears in Collections:Bachelor thesis, research projects, etc.

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