Please use this identifier to cite or link to this item:
http://hdl.handle.net/10609/147467
Title: | Estimación del coste del gas en transacciones de Ethereum mediante Deep Learning |
Author: | Arias-Sánchez, Antonio ![]() |
Tutor: | Lopez Vicario, Jose ![]() |
Others: | Vilajosana, Xavier ![]() |
Abstract: | This work studies the application of Deep Learning techniques to Ethereum blockchain Gas price prediction. After a brief introduction to Deep Learning and Ethereum Blockchain, a literature review and search of related works is performed. Then, a Machine Learning scenario is proposed, where the gas price is to be predicted from several Ethereum blockchain parameters that seem relevant. A data source from where to get historical datasets has been identified, and scripts have been prepared to retrieve and prepare them. A preliminary data analysis is then performed on them. Subsequently, several models and Artificial Neural Networks are proposed, created and trained with the previous datasets, and their results compared and commented. Lastly, conclusions, and possible additional study lines, are presented. |
Keywords: | blockchain Ethereum deep learning |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | Feb-2022 |
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 | |
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antariasTFM0123memoria.pdf | Memoria del TFM | 2,04 MB | Adobe PDF | ![]() View/Open |
antariasTFM0123presentacion.pdf | Presentación del TFM | 968,05 kB | Adobe PDF | ![]() View/Open |
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