Agrometeorological forecast and agriculture in Boyacá

Authors

  • Jairo Amador Fundación Universitaria Juan de Castellanos

Keywords:

Date, information, knowledge, data mining and meteorology.

Abstract

The region from Boyacá is not aside from the negative effects of the climate change which generate problems to the agriculture, economic sector that receives the biggest impact. For that reason it is urgent to develop the Agrometeorological Prediction (PA), in order to adopt measures that allow to reduce the vulnerability of the sector before icy, long periods of summer or rains, etc.. In this context, the Group of Artificial intelligence of the University Juan of Castellanos GIA-JDC, outlines this scientific project to improve the precision of the agrometeorological indicators by means of the development of a methodology that includes Artificial intelligence techniques (data Mining, diffuse logic and genetic algorithms). This article shows the first phase of the work, trying to expose where, how and when to apply the most outstanding theory in the obtaining of knowledge and its incidence in the proposed methodology for the investigation development.

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Author Biography

Jairo Amador, Fundación Universitaria Juan de Castellanos

M.Sc. en Ciencias Computacionales, Universidad Autónoma de Bucaramanga y TEC de Monterrey México. Especialista en Telemática, UNIBOYACA. Licenciado en Matemáticas y Física. Ingeniero de Sistemas. Universidad Pedagógica y Tecnológica de Colombia, Docente Investigador Fundación Universitaria Juan de Castellanos.

References

•AMADOR, J. y PINEDA, W. (2006). Diseño y desarrollo de algoritmos y sistemas de control por clonación artificial de un sensor de viscosidad. Bucaramanga. 193 p. Tesis (Magíster en Ciencias Computacionales). Instituto Tecnológico y de Estudios Superiores de Monterrey México y Universidad Autónoma de Bucaramanga
•PYLE, D. (1999). Data Preparation for Data Mining. Morgan Kaufmann.
•FAYYAD, et al. (1996). Advances in Knowledge Discovery and Data Mining. AAAI Press / The MIT Press.
•IAN H. WITTEN & EIBE FRANK. (1999). Data Mining: Practical Maching Learning Tools and Techniques with java implementations. Morgan Kaufmann.
•Organización Meteorológica Mundial. (2004). Servicios de Información y Predicción del Clima (SIPC) y Aplicaciones Agrometeorológicas para los Países Andinos. Actas de la Reunión Técnica llevada a cabo en Guayaquil, Ecuador, del 8 al 12 de diciembre de 2003. Ginebra: Organización Metereológica Mundial. Consultada el 20 de febrero/07.

Published

2007-10-29

How to Cite

Amador, J. (2007). Agrometeorological forecast and agriculture in Boyacá. Cultura científica, (5), 45–48. Retrieved from https://jdc-ojs.vobomkt.com/index.php/Cult_cient/article/view/321

Issue

Section

Article of scientific and technological research