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Classification of containers with Aedes aegypti pupae using a Neural Networks model
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 appr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6072124/ https://www.ncbi.nlm.nih.gov/pubmed/30036370 http://dx.doi.org/10.1371/journal.pntd.0006592 |
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author | Medronho, Roberto de Andrade Câmara, Volney de Magalhães Macrini, Leonardo |
author_facet | Medronho, Roberto de Andrade Câmara, Volney de Magalhães Macrini, Leonardo |
author_sort | Medronho, Roberto de Andrade |
collection | PubMed |
description | 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 method, a model with the capacity to emulate non-linear data, got better results in comparison with the discriminant power of the Logistic Regression model. Thus, the outcomes of using the Neural Networks method achieved better separability in classifying the containers with pupae and those with no pupae. CONCLUSION: This type of analysis will aid in the efforts to design an efficient program to control Aedes aegypti that can concentrate principally on containers which present the greatest productivity. |
format | Online Article Text |
id | pubmed-6072124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-60721242018-08-16 Classification of containers with Aedes aegypti pupae using a Neural Networks model Medronho, Roberto de Andrade Câmara, Volney de Magalhães Macrini, Leonardo PLoS Negl Trop Dis Research Article 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 method, a model with the capacity to emulate non-linear data, got better results in comparison with the discriminant power of the Logistic Regression model. Thus, the outcomes of using the Neural Networks method achieved better separability in classifying the containers with pupae and those with no pupae. CONCLUSION: This type of analysis will aid in the efforts to design an efficient program to control Aedes aegypti that can concentrate principally on containers which present the greatest productivity. Public Library of Science 2018-07-23 /pmc/articles/PMC6072124/ /pubmed/30036370 http://dx.doi.org/10.1371/journal.pntd.0006592 Text en © 2018 Medronho et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Medronho, Roberto de Andrade Câmara, Volney de Magalhães Macrini, Leonardo Classification of containers with Aedes aegypti pupae using a Neural Networks model |
title | Classification of containers with Aedes aegypti pupae using a Neural Networks model |
title_full | Classification of containers with Aedes aegypti pupae using a Neural Networks model |
title_fullStr | Classification of containers with Aedes aegypti pupae using a Neural Networks model |
title_full_unstemmed | Classification of containers with Aedes aegypti pupae using a Neural Networks model |
title_short | Classification of containers with Aedes aegypti pupae using a Neural Networks model |
title_sort | classification of containers with aedes aegypti pupae using a neural networks model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6072124/ https://www.ncbi.nlm.nih.gov/pubmed/30036370 http://dx.doi.org/10.1371/journal.pntd.0006592 |
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