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Prediction of the Efficiency for Decision Making in the Agricultural Sector Through Artificial Intelligence

Conference paper
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Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1245)

Abstract

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.

Keywords

Neural networks Agricultural activity Precision agriculture Decision making Prediction analysis 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.Universidad de La CostaBarranquillaColombia
  2. 2.Universidad Simón BolívarBarranquillaColombia
  3. 3.Universidad LibreSan Pedro SulaHonduras
  4. 4.Corporación Universitaria Minuto de Dios. UNIMINUTOBarranquillaColombia
  5. 5.Corporación Universitaria LatinoamericanaBarranquillaColombia

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