Earticle

초록

영어

The analysis of pesticide residues in food has become, very important in recent years because of the damage they may cause in human health. The analysis of residues requires, different equipment and software for the study, characterization, identification and quantification of these chemicals. However not always the desired parameters according to the method implemented are obtained, so the estimation of these is an optimal solution, considering the short runtime. Parameter estimation, is a tool used heavily in different fields and applications, in order to obtain, an unknown value from variables related. Estimating pesticide retention times Carbamates, by a trained neural network by the method of particle swarm, is presented in this work. The data for network training were acquired through a study of levels of pesticide residues present in samples of kidney tomato (Lycopersicon esculentum).

목차

Abstract
 1. Introduction
 2. Methods
  2.1 Particle Swarm Optimization
  2.2 Neuronal Network Characteristics
 3. Results and Discussion
 4. Conclusions
 Acknowledgment
 References

키워드

저자

• Angélica Palacios [ Universidad Militar Nueva Granada ]
• Olga Ramos [ Universidad Militar Nueva Granada ]
• Darío Amaya [ Universidad Militar Nueva Granada ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605