Classification of containers with Aedes aegypti pupae using a Neural Networks model.

ABSTRACT:

Introduction

This paper discusses the presence of Aedes aegypti pupae in different types of containers considering: volume, pH of the container, among other variables.

Methods

A nonlinear method for selection was applied, based on Mutual Information, by placing in order of importance the most appropriate variables for identifying containers with and without Aedes aegypti pupae. Such variables were used for input into a Neural Network in layers for classification.

Results

Among the experiments carried out, the best result obtained used the first eight variables selected by order of importance. The percentage of hits for containers which had no Aedes aegypti pupae was 73.3%, and 80.9% for those which did have Aedes aegypti pupae in the containers. This Neural Network me

SUBMITTER: Medronho RA 

PROVIDER: S-EPMC6072124 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature