Pisum sativum classification based on a methodological approach for pattern recognition using discriminant analysis and neural networks

Authors:
Anna Pérez-Méndez;Ronald Maldonado-Rodríguez;Elizabeth Torres-Rivas;Francklin Rivas-Echeverría
Affiliations:
Escuela de Estadística, Universidad de Los Andes, Mérida, Venezuela;Bioenergetic Laboratory, University of Geneva, Switzerland;Escuela de Estadística, Universidad de Los Andes, Mérida, Venezuela;Laboratorio de Sistemas Inteligentes, Universidad de Los Andes, Switzerland
Venue:
NN'05 Proceedings of the 6th WSEAS international conference on Neural networks
Year:
2005

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Neural network design

Neural network design
A methodological approach for pattern recognition system using discriminant analysis and artificial neural networks

NN'05 Proceedings of the 6th WSEAS international conference on Neural networks

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Abstract

In this work a statistical analysis-based methodological approach for a pattern recognition system using discriminant analysis and neural networks is used for the classification of Pisum sativum (peas) according to the drought resistance. The statistical techniques used in the exploratory analysis are a fundamental tool in the creation of variables sets and observations for the model adjustment in the neural models and in the discriminant models.