Félix Vásquez

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Fuzzy based models have been used in many areas of research. One issue with these models is that rule bases have the potential for indiscriminant growth. Inference systems with large number of rules can be overspecified, have model comprehension issues and suffer from bad performance. In this research we investigate the use of a genetic algorithm towards(More)
This paper describes a neural network based inference system developed as part of a bioinformatic application in order to help implement a systematic search scheme for the identification of genes which encode enzymes of metabolic pathways. The inference system uses BLAST sequence alignment values as inputs and generates a classification of the best(More)
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