Unidades Recurrentes Cerradas (GRU) vs Redes Neuronales Artificiales en la predicción de la generación Eléctrica de la Central Hidroeléctrica Illuchi.
The prediction of events has been, since ancient times, a phenomenon capable of generating curiosity in human beings, however, to achieve a projection of a future event, a detailed analysis of data is required to predict subsequent events, with this idea. Objectives: The objective of the research wa...
שמור ב:
| מחבר ראשי: | |
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| פורמט: | masterThesis |
| שפה: | spa |
| יצא לאור: |
2023
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| נושאים: | |
| גישה מקוונת: | http://repositorio.utc.edu.ec/handle/27000/10774 |
| תגים: |
הוספת תג
אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!
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הוספת תג | סיכום: | The prediction of events has been, since ancient times, a phenomenon capable of generating curiosity in human beings, however, to achieve a projection of a future event, a detailed analysis of data is required to predict subsequent events, with this idea. Objectives: The objective of the research was to develop two prediction systems by applying artificial neural networks and GRU to determine the predicted electricity generation at the ILLUCHI HYDROELECTRIC PLANT. Methodology: The data used for this study was collected from ELEPCO S.A. operators. based on the years 2008 - 2020. The input variables were the date and the energy generated to develop different cases with different conditions in order to reach a possible successful Recurrent Neural Network model. Results: Once the model variables were understood, the data were divided into two groups: training 70% and validation 30% respectively. For the corresponding training, the ADAM algorithm and the libraries provided by Python were used. |
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