Prediction of the efficiency for decision making in the agricultural sector through artificial intelligence
Agriculture plays an important role in Latin American countries where the demand for provisions to reduce hunger and poverty represents a significant priority in order to improve the development and quality of life in the region. In this research, linear data analysis techniques and soil classificat...
- Autores:
-
Viloria, Amelec
Ruiz Lázaro, Alex
Echeverría González, Ana Maria
Pineda Lezama, Omar Bonerge
Lamby Barrios, Juan Guillermo
Leon Castro, Nadia
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2021
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7711
- Acceso en línea:
- https://hdl.handle.net/11323/7711
https://doi.org/10.1007/978-981-15-7234-0_91
https://repositorio.cuc.edu.co/
- Palabra clave:
- Neural networks
Agricultural activity
Precision agriculture
Decision making
Prediction analysis
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International
| Summary: | Agriculture plays an important role in Latin American countries where the demand for provisions to reduce hunger and poverty represents a significant priority in order to improve the development and quality of life in the region. In this research, linear data analysis techniques and soil classification are reviewed through neural networks for decision making in agriculture. The results permit to conclude that precision agriculture, observation and control technologies are gaining ground, making it possible to determine the production demand in these countries |
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