Application of fuzzy logic for the evaluation of livestock slaughtering

Detalhes bibliográficos
Autor(a) principal: Gabriel Filho,Luís R. A.
Data de Publicação: 2011
Outros Autores: Cremasco,Camila P., Putti,Fernando F., Chacur,Marcelo G. M.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Engenharia Agrícola
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162011000400019
Resumo: The fuzzy logic admits infinite intermediate logical values between false and true. With this principle, it developed in this study a system based on fuzzy rules, which indicates the body mass index of ruminant animals in order to obtain the best time to slaughter. The controller developed has as input the variables weight and height, and as output a new body mass index, called Fuzzy Body Mass Index (Fuzzy BMI), which may serve as a detection system at the time of livestock slaughtering, comparing one another by the linguistic variables "Very Low", "Low", "Average ", "High" and "Very High". For demonstrating the use application of this fuzzy system, an analysis was made with 147 Nellore beeves to determine Fuzzy BMI values for each animal and indicate the location of body mass of any herd. The performance validation of the system was based on a statistical analysis using the Pearson correlation coefficient of 0.923, representing a high positive correlation, indicating that the proposed method is appropriate. Thus, this method allows the evaluation of the herd comparing each animal within the group, thus providing a quantitative method of farmer decision. It was concluded that this study established a computational method based on fuzzy logic that mimics part of human reasoning and interprets the body mass index of any bovine species and in any region of the country.
id SBEA-1_2946ad076a3bfc7e1f81e4d5e8801f90
oai_identifier_str oai:scielo:S0100-69162011000400019
network_acronym_str SBEA-1
network_name_str Engenharia Agrícola
repository_id_str
spelling Application of fuzzy logic for the evaluation of livestock slaughteringcorporal indexcontrolling mass fuzzyquantitative methodThe fuzzy logic admits infinite intermediate logical values between false and true. With this principle, it developed in this study a system based on fuzzy rules, which indicates the body mass index of ruminant animals in order to obtain the best time to slaughter. The controller developed has as input the variables weight and height, and as output a new body mass index, called Fuzzy Body Mass Index (Fuzzy BMI), which may serve as a detection system at the time of livestock slaughtering, comparing one another by the linguistic variables "Very Low", "Low", "Average ", "High" and "Very High". For demonstrating the use application of this fuzzy system, an analysis was made with 147 Nellore beeves to determine Fuzzy BMI values for each animal and indicate the location of body mass of any herd. The performance validation of the system was based on a statistical analysis using the Pearson correlation coefficient of 0.923, representing a high positive correlation, indicating that the proposed method is appropriate. Thus, this method allows the evaluation of the herd comparing each animal within the group, thus providing a quantitative method of farmer decision. It was concluded that this study established a computational method based on fuzzy logic that mimics part of human reasoning and interprets the body mass index of any bovine species and in any region of the country.Associação Brasileira de Engenharia Agrícola2011-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162011000400019Engenharia Agrícola v.31 n.4 2011reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/S0100-69162011000400019info:eu-repo/semantics/openAccessGabriel Filho,Luís R. A.Cremasco,Camila P.Putti,Fernando F.Chacur,Marcelo G. M.eng2011-09-22T00:00:00Zoai:scielo:S0100-69162011000400019Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2011-09-22T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false
dc.title.none.fl_str_mv Application of fuzzy logic for the evaluation of livestock slaughtering
title Application of fuzzy logic for the evaluation of livestock slaughtering
spellingShingle Application of fuzzy logic for the evaluation of livestock slaughtering
Gabriel Filho,Luís R. A.
corporal index
controlling mass fuzzy
quantitative method
title_short Application of fuzzy logic for the evaluation of livestock slaughtering
title_full Application of fuzzy logic for the evaluation of livestock slaughtering
title_fullStr Application of fuzzy logic for the evaluation of livestock slaughtering
title_full_unstemmed Application of fuzzy logic for the evaluation of livestock slaughtering
title_sort Application of fuzzy logic for the evaluation of livestock slaughtering
author Gabriel Filho,Luís R. A.
author_facet Gabriel Filho,Luís R. A.
Cremasco,Camila P.
Putti,Fernando F.
Chacur,Marcelo G. M.
author_role author
author2 Cremasco,Camila P.
Putti,Fernando F.
Chacur,Marcelo G. M.
author2_role author
author
author
dc.contributor.author.fl_str_mv Gabriel Filho,Luís R. A.
Cremasco,Camila P.
Putti,Fernando F.
Chacur,Marcelo G. M.
dc.subject.por.fl_str_mv corporal index
controlling mass fuzzy
quantitative method
topic corporal index
controlling mass fuzzy
quantitative method
description The fuzzy logic admits infinite intermediate logical values between false and true. With this principle, it developed in this study a system based on fuzzy rules, which indicates the body mass index of ruminant animals in order to obtain the best time to slaughter. The controller developed has as input the variables weight and height, and as output a new body mass index, called Fuzzy Body Mass Index (Fuzzy BMI), which may serve as a detection system at the time of livestock slaughtering, comparing one another by the linguistic variables "Very Low", "Low", "Average ", "High" and "Very High". For demonstrating the use application of this fuzzy system, an analysis was made with 147 Nellore beeves to determine Fuzzy BMI values for each animal and indicate the location of body mass of any herd. The performance validation of the system was based on a statistical analysis using the Pearson correlation coefficient of 0.923, representing a high positive correlation, indicating that the proposed method is appropriate. Thus, this method allows the evaluation of the herd comparing each animal within the group, thus providing a quantitative method of farmer decision. It was concluded that this study established a computational method based on fuzzy logic that mimics part of human reasoning and interprets the body mass index of any bovine species and in any region of the country.
publishDate 2011
dc.date.none.fl_str_mv 2011-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162011000400019
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162011000400019
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0100-69162011000400019
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Engenharia Agrícola
publisher.none.fl_str_mv Associação Brasileira de Engenharia Agrícola
dc.source.none.fl_str_mv Engenharia Agrícola v.31 n.4 2011
reponame:Engenharia Agrícola
instname:Associação Brasileira de Engenharia Agrícola (SBEA)
instacron:SBEA
instname_str Associação Brasileira de Engenharia Agrícola (SBEA)
instacron_str SBEA
institution SBEA
reponame_str Engenharia Agrícola
collection Engenharia Agrícola
repository.name.fl_str_mv Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)
repository.mail.fl_str_mv revistasbea@sbea.org.br||sbea@sbea.org.br
_version_ 1752126270607458304