Extracción de modelos inteligentes a partir de datos con aplicación en sistemas agrícolas
Fecha
2009-06-16
Autores
Herrera Contreras, Carlos Rafael
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Editor
Universidad Central “Marta Abreu” de Las Villas
Resumen
La presente investigación tiene como propósito mostrar el procedimiento utilizado para la predicción y pronóstico de variables agro meteorológicas asociadas a sistemas productivos agrícolas, tales como el rendimiento en cultivos y sus componentes. Se emplea los sistemas difusos como la base para determinar los correspondientes modelos predictivos. Estos modelos fueron construidos usando la técnica conocida como agrupamiento difuso. La temperatura y humedad relativa fueron las dos variables de un sistema agro meteorológico usadas en esta investigación para el ensayo y ajuste del algoritmo y programa para el pronóstico de variables. Ambas variables formarán parte de un sistema multiagente. Finalmente se concibe la implementación de sistema multiagente para el pronóstico del rendimiento.
This research aims to show the procedure used for the prediction and prognosis of agro meteorological variables associated with agricultural production systems, such as crop yield and its components. Fuzzy systems is used as the basis for determining appropriate predictive models. These models were constructed using the technique known as fuzzy clustering. The temperature and relative humidity were the variables of an agrometeorological system used in this research for testing and tuning of the algorithm and program to variables forecasting. Both variables are part of a multiagent system. Finally sees the implementation of multiagent system for yield prediction
This research aims to show the procedure used for the prediction and prognosis of agro meteorological variables associated with agricultural production systems, such as crop yield and its components. Fuzzy systems is used as the basis for determining appropriate predictive models. These models were constructed using the technique known as fuzzy clustering. The temperature and relative humidity were the variables of an agrometeorological system used in this research for testing and tuning of the algorithm and program to variables forecasting. Both variables are part of a multiagent system. Finally sees the implementation of multiagent system for yield prediction
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Palabras clave
Extracción de Datos, Modelos Inteligentes, Agrupamiento Difuso, Sistema Multiagente, Sistemas Agrícolas, Inteligencia Artificial