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Bachelor thesis

Publication date

2018-06-27

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cc-by-nc-nd (c) Núria Casals Lladó, 2018
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/124823

Xarxes neuronals recurrents per a sèries temporals

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Abstract

[en] Recurrent neural networks (RNNs) have been widely used for processing sequential data and are capable of learning long-term dependencies. This project proceeds from its inception, studying the behaviour of the simplest Deep Learning structures, to learning issues associated with time series data analysis to finally achieve more complex architectures: Long Short-Term Memory and Gated Recurrent Units. A model with a Gated Recurrent Unit has been implemented to forecast time series data associated with electricity consumption.

Description

Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2018, Director: Josep Fortiana Gregori,

Subject

Xarxes neuronals (Informàtica), Treballs de fi de grau, Algorismes computacionals, Anàlisi de sèries temporals, Aprenentatge automàtic, Energia elèctrica

Subject (English)

Neural networks (Computer science), Bachelor's theses, Computer algorithms, Time-series analysis, Machine learning, Electric power

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Treballs Finals de Grau (TFG) - Matemàtiques
Programari - Treballs de l'alumnat

Citation

CASALS LLADÓ, Núria. Xarxes neuronals recurrents per a sèries temporals. [consulted: 8 of June of 2026]. Available at: https://hdl.handle.net/2445/124823

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