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http://hdl.handle.net/10609/150599
Title: | Utilización de Machine Learning para proporcionar a los deportistas acuáticos herramientas innovadoras para la selección del aparejo a utilizar |
Author: | Sánchez La O, Benjamín Carmelo |
Tutor: | Andrés Sanz, Humberto |
Others: | Daradoumis, Thanasis |
Abstract: | The present work focuses on the development of a Machine Learning (ML) based algorithm called WindCaddy, aimed at improving decision making in wind-driven water sports, such as windsurfing. Using meteorological data provided by the Spanish Meteorological Agency (AEMET), predictive analysis algorithms are implemented to recommend the optimal equipment according to wind and water conditions. The methodology ranges from data collection and processing to the validation of the developed models. Machine learning techniques are used and customised algorithms are developed for the selection of the appropriate rig for each session. The results show a significant improvement in the accuracy of equipment recommendations compared to traditional methods. The benefits in terms of performance and safety for athletes are highlighted. In conclusion, WindCaddy offers an innovative solution that fuses a passion for water sports with data analytics technologies, enhancing the athlete experience and providing tools for informed and optimised decision making. |
Keywords: | windsurf caddie ccondiciones |
Document type: | info:eu-repo/semantics/bachelorThesis |
Issue Date: | 16-Jun-2024 |
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 | |
---|---|---|---|---|
TFG_code.zip | Código desarrollado | 30,86 MB | Fichero comprimido en ZIP | View/Open |
README.txt | Fichero léeme. | 474 B | Text | View/Open |
bsanlaoTFG0624memoria.pdf | Memoria del TFG | 4,13 MB | Adobe PDF | View/Open |
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