Comparison Between Machine Learning Models for Yield Forecast in Cocoa Crops in Santander, Colombia
The identification of influencing factors in crop yield (kg·ha-1) provides essential information for decision-making processes related to the prediction and improvement of productivity, which gives farmers the opportunity to increase their income. The current study investigates the application of mu...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad Pedagógica y Tecnológica de Colombia
- Repositorio:
- RiUPTC: Repositorio Institucional UPTC
- Idioma:
- eng
spa
- OAI Identifier:
- oai:repositorio.uptc.edu.co:001/14270
- Acceso en línea:
- https://revistas.uptc.edu.co/index.php/ingenieria/article/view/10853
https://repositorio.uptc.edu.co/handle/001/14270
- Palabra clave:
- agricultural-yield
agroforestry-system
cocoa
machine-learning
prediction
productivity
aprendizaje-automático
cacao
predicción
productividad
rendimientos-agrícolas
sistemas-agroforestales
- Rights
- License
- Copyright (c) 2020 Henry Lamos-Díaz; David-Esteban Puentes-Garzón; Diego-Alejandro Zarate-Caicedo