Historical milk production performance in São Paulo State municipalities between 2005 and 2015 using Artificial Intelligence
This study analyzes the use of Artificial Intelligence on milk production chain, aiming at identifying patterns of their characteristics in 645 municipalities of the State of São Paulo taking into account produced milk categories. Using information from secondary sources, it was used the Optimum-Pat...
Main Authors: | , |
---|---|
Format: | Article |
Language: | Portuguese |
Published: |
Universidade Estadual Paulista Júlio de Mesquita Filho
2016-12-01
|
Series: | Revista Eletrônica Competências Digitais para Agricultura Familiar |
Subjects: | |
Online Access: | http://codaf.tupa.unesp.br:8082/index.php/recodaf/article/view/34 |
id |
doaj-5f57a5019fb247abaca36e1257e2faf1 |
---|---|
record_format |
Article |
spelling |
doaj-5f57a5019fb247abaca36e1257e2faf12020-11-24T20:58:12ZporUniversidade Estadual Paulista Júlio de Mesquita FilhoRevista Eletrônica Competências Digitais para Agricultura Familiar2448-04522016-12-0122395123Historical milk production performance in São Paulo State municipalities between 2005 and 2015 using Artificial IntelligencePatrícia de Freitas Pelozo0Rafael Medeiros Hespanhol1Universidade do Oeste Paulista (UNOESTE)Faculdade de Tecnologia de Presidente Prudente (FATEC)This study analyzes the use of Artificial Intelligence on milk production chain, aiming at identifying patterns of their characteristics in 645 municipalities of the State of São Paulo taking into account produced milk categories. Using information from secondary sources, it was used the Optimum-Path Forest method (OPF) to identify milk production characteristics clusters. The analyzed data were the amount of milk produced in the rural properties according to their categories regarding quality making possible to suggest training adequacies and public bodies actions regarding rural producers, more focused on the reality of each municipality and secondarily, it was possible to test the OPF use as a decision-making tool at the agroindustrial sector.http://codaf.tupa.unesp.br:8082/index.php/recodaf/article/view/34Cadeias ProdutivaLeiteFloresta de Caminhos ÓtimosClusterização |
collection |
DOAJ |
language |
Portuguese |
format |
Article |
sources |
DOAJ |
author |
Patrícia de Freitas Pelozo Rafael Medeiros Hespanhol |
spellingShingle |
Patrícia de Freitas Pelozo Rafael Medeiros Hespanhol Historical milk production performance in São Paulo State municipalities between 2005 and 2015 using Artificial Intelligence Revista Eletrônica Competências Digitais para Agricultura Familiar Cadeias Produtiva Leite Floresta de Caminhos Ótimos Clusterização |
author_facet |
Patrícia de Freitas Pelozo Rafael Medeiros Hespanhol |
author_sort |
Patrícia de Freitas Pelozo |
title |
Historical milk production performance in São Paulo State municipalities between 2005 and 2015 using Artificial Intelligence |
title_short |
Historical milk production performance in São Paulo State municipalities between 2005 and 2015 using Artificial Intelligence |
title_full |
Historical milk production performance in São Paulo State municipalities between 2005 and 2015 using Artificial Intelligence |
title_fullStr |
Historical milk production performance in São Paulo State municipalities between 2005 and 2015 using Artificial Intelligence |
title_full_unstemmed |
Historical milk production performance in São Paulo State municipalities between 2005 and 2015 using Artificial Intelligence |
title_sort |
historical milk production performance in são paulo state municipalities between 2005 and 2015 using artificial intelligence |
publisher |
Universidade Estadual Paulista Júlio de Mesquita Filho |
series |
Revista Eletrônica Competências Digitais para Agricultura Familiar |
issn |
2448-0452 |
publishDate |
2016-12-01 |
description |
This study analyzes the use of Artificial Intelligence on milk production chain, aiming at identifying patterns of their characteristics in 645 municipalities of the State of São Paulo taking into account produced milk categories. Using information from secondary sources, it was used the Optimum-Path Forest method (OPF) to identify milk production characteristics clusters. The analyzed data were the amount of milk produced in the rural properties according to their categories regarding quality making possible to suggest training adequacies and public bodies actions regarding rural producers, more focused on the reality of each municipality and secondarily, it was possible to test the OPF use as a decision-making tool at the agroindustrial sector. |
topic |
Cadeias Produtiva Leite Floresta de Caminhos Ótimos Clusterização |
url |
http://codaf.tupa.unesp.br:8082/index.php/recodaf/article/view/34 |
work_keys_str_mv |
AT patriciadefreitaspelozo historicalmilkproductionperformanceinsaopaulostatemunicipalitiesbetween2005and2015usingartificialintelligence AT rafaelmedeiroshespanhol historicalmilkproductionperformanceinsaopaulostatemunicipalitiesbetween2005and2015usingartificialintelligence |
_version_ |
1716786216714633216 |