Estimación del peso de racimos de banano por medio de algoritmos de aprendizaje automático
This research develops a predictive model using machine learning techniques to estimate the weight of the banana bunch, given its importance as the key food and Ecuador's world leadership in exports. Conducted in Mata de Cacao, Los Ríos province, using exploratory, judgment and descriptive meth...
שמור ב:
| מחבר ראשי: | |
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| פורמט: | bachelorThesis |
| שפה: | spa |
| יצא לאור: |
2024
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| נושאים: | |
| גישה מקוונת: | https://repositorio.uteq.edu.ec/handle/43000/7229 |
| תגים: |
הוספת תג
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הוספת תג | סיכום: | This research develops a predictive model using machine learning techniques to estimate the weight of the banana bunch, given its importance as the key food and Ecuador's world leadership in exports. Conducted in Mata de Cacao, Los Ríos province, using exploratory, judgment and descriptive methods to identify significant variables in bunch weight, such as upper and lower calibration, hands, lot, age, and maximum and minimum temperature. Five algorithms are applied, including Enhanced Gradient Regression, Ridge Regression, Nearest Neighbor Regression, Lasso Regression and Gradient Boosting Machine with Light Tree Implementation. Highlighting the effectiveness of the Gradient Boosting Machine with Light Tree Implementation algorithm, this approach contributes to improved agricultural management and crop planning. |
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