Please use this identifier to cite or link to this item:
http://hdl.handle.net/10609/138247
Title: | Aplicación de Machine Learning al consumo eléctrico de edificios inteligentes |
Author: | Meneses Díez, Mónica |
Tutor: | Crespo García, David |
Others: | Monzo, Carlos |
Abstract: | Nowadays, the consumption of electricity is necessary in every person's daily life. Therefore, electricity consumption has become a necessity for society. In this work, we study the prediction of electricity consumption in buildings using Machine Learning. Thus, from a large amount of electricity consumption data in buildings, it will be possible to make a prediction of consumption using Machine Learning. The aim is to study the different supervised and unsupervised learning models that can be applied to this type of consumption data in order to obtain the best prediction, given that many of these data have zero value, and therefore the model applied in this type of predictions may be biased. Furthermore, the data obtained can be used to improve energy efficiency and take measures to make the most of renewable energies by reducing the costs associated with traditional electricity consumption. |
Keywords: | electricity consumption machine learning energy efficiency |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | 27-Dec-2021 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Bachelor thesis, research projects, etc. |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
mmenesesdTFM0122memoria.pdf | Memoria del TFM | 1,04 MB | Adobe PDF | View/Open |
Share:
This item is licensed under a Creative Commons License