ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO THE OPTIMIZATION OF MICRO-IRRIGATION SYSTEMS BY THE ZIMMERMANN-WERNER METHOD
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Engenharia Agrícola |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162022000800111 |
Resumo: | ABSTRACT Optimal solutions derived from linear programming models depend entirely on input parameters, which may present some imprecision because they come from estimates. Fuzzy linear programming allows the incorporation of these uncertainties in linear models, which can include the flexibility of resources, costs, goals, and constraints. This paper aimed to show new optimal solutions for a model to minimize the equivalent annual cost of micro-irrigation systems on sloping terrains. The Zimmermann-Werner fuzzy linear programming method, whose objective function is diffuse due to the restrictions of the hydraulic network being dispersed, was used. Sixty models were created and all solutions were satisfactory, with an annual cost of the irrigation system lower than the original model. The lowest value was US$ 238.74 ha-1, which occurred on the 3% slope. A reduction was observed in the annual cost due to the increased use of pipes with a 50-mm nominal diameter in the secondary line. Thus, fuzzy linear programming provided better solutions with small modifications to the irrigation system, while maintaining all hydraulic network requirements for proper system operation. |
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Engenharia Agrícola |
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ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO THE OPTIMIZATION OF MICRO-IRRIGATION SYSTEMS BY THE ZIMMERMANN-WERNER METHODdrip irrigation designfuzzy linear optimizationflexibility restrictionsdecrease in annual costsABSTRACT Optimal solutions derived from linear programming models depend entirely on input parameters, which may present some imprecision because they come from estimates. Fuzzy linear programming allows the incorporation of these uncertainties in linear models, which can include the flexibility of resources, costs, goals, and constraints. This paper aimed to show new optimal solutions for a model to minimize the equivalent annual cost of micro-irrigation systems on sloping terrains. The Zimmermann-Werner fuzzy linear programming method, whose objective function is diffuse due to the restrictions of the hydraulic network being dispersed, was used. Sixty models were created and all solutions were satisfactory, with an annual cost of the irrigation system lower than the original model. The lowest value was US$ 238.74 ha-1, which occurred on the 3% slope. A reduction was observed in the annual cost due to the increased use of pipes with a 50-mm nominal diameter in the secondary line. Thus, fuzzy linear programming provided better solutions with small modifications to the irrigation system, while maintaining all hydraulic network requirements for proper system operation.Associação Brasileira de Engenharia Agrícola2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162022000800111Engenharia Agrícola v.42 n.spe 2022reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v42nepe20210118/2022info:eu-repo/semantics/openAccessCastro,Evanize R.Saad,João C. C.Gabriel Filho,Luís R. A.eng2022-04-28T00:00:00Zoai:scielo:S0100-69162022000800111Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2022-04-28T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO THE OPTIMIZATION OF MICRO-IRRIGATION SYSTEMS BY THE ZIMMERMANN-WERNER METHOD |
title |
ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO THE OPTIMIZATION OF MICRO-IRRIGATION SYSTEMS BY THE ZIMMERMANN-WERNER METHOD |
spellingShingle |
ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO THE OPTIMIZATION OF MICRO-IRRIGATION SYSTEMS BY THE ZIMMERMANN-WERNER METHOD Castro,Evanize R. drip irrigation design fuzzy linear optimization flexibility restrictions decrease in annual costs |
title_short |
ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO THE OPTIMIZATION OF MICRO-IRRIGATION SYSTEMS BY THE ZIMMERMANN-WERNER METHOD |
title_full |
ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO THE OPTIMIZATION OF MICRO-IRRIGATION SYSTEMS BY THE ZIMMERMANN-WERNER METHOD |
title_fullStr |
ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO THE OPTIMIZATION OF MICRO-IRRIGATION SYSTEMS BY THE ZIMMERMANN-WERNER METHOD |
title_full_unstemmed |
ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO THE OPTIMIZATION OF MICRO-IRRIGATION SYSTEMS BY THE ZIMMERMANN-WERNER METHOD |
title_sort |
ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO THE OPTIMIZATION OF MICRO-IRRIGATION SYSTEMS BY THE ZIMMERMANN-WERNER METHOD |
author |
Castro,Evanize R. |
author_facet |
Castro,Evanize R. Saad,João C. C. Gabriel Filho,Luís R. A. |
author_role |
author |
author2 |
Saad,João C. C. Gabriel Filho,Luís R. A. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Castro,Evanize R. Saad,João C. C. Gabriel Filho,Luís R. A. |
dc.subject.por.fl_str_mv |
drip irrigation design fuzzy linear optimization flexibility restrictions decrease in annual costs |
topic |
drip irrigation design fuzzy linear optimization flexibility restrictions decrease in annual costs |
description |
ABSTRACT Optimal solutions derived from linear programming models depend entirely on input parameters, which may present some imprecision because they come from estimates. Fuzzy linear programming allows the incorporation of these uncertainties in linear models, which can include the flexibility of resources, costs, goals, and constraints. This paper aimed to show new optimal solutions for a model to minimize the equivalent annual cost of micro-irrigation systems on sloping terrains. The Zimmermann-Werner fuzzy linear programming method, whose objective function is diffuse due to the restrictions of the hydraulic network being dispersed, was used. Sixty models were created and all solutions were satisfactory, with an annual cost of the irrigation system lower than the original model. The lowest value was US$ 238.74 ha-1, which occurred on the 3% slope. A reduction was observed in the annual cost due to the increased use of pipes with a 50-mm nominal diameter in the secondary line. Thus, fuzzy linear programming provided better solutions with small modifications to the irrigation system, while maintaining all hydraulic network requirements for proper system operation. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
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=S0100-69162022000800111 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162022000800111 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1809-4430-eng.agric.v42nepe20210118/2022 |
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.42 n.spe 2022 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_ |
1752126275486482432 |