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: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1590/1809-4430-ENG.AGRIC.V42NEPE20210118/2022 http://hdl.handle.net/11449/240147 |
Resumo: | 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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Repositório Institucional da UNESP |
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ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO THE OPTIMIZATION OF MICRO-IRRIGATION SYSTEMS BY THE ZIMMERMANN-WERNER METHODdecrease in annual costsDrip irrigation designflexibility restrictionsfuzzy linear optimizationOptimal 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.São Paulo State University (UNESP), SPSão Paulo State University (UNESP), SPUniversidade Estadual Paulista (UNESP)Castro, Evanize R. [UNESP]Saad, João C. C. [UNESP]Gabriel Filho, Luís R. A. [UNESP]2023-03-01T20:03:26Z2023-03-01T20:03:26Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1590/1809-4430-ENG.AGRIC.V42NEPE20210118/2022Engenharia Agricola, v. 42, n. Special Issue, 2022.1809-44300100-6916http://hdl.handle.net/11449/24014710.1590/1809-4430-ENG.AGRIC.V42NEPE20210118/20222-s2.0-85130855387Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEngenharia Agricolainfo:eu-repo/semantics/openAccess2023-03-01T20:03:26Zoai:repositorio.unesp.br:11449/240147Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-06T00:11:47.739615Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)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. [UNESP] decrease in annual costs Drip irrigation design flexibility restrictions fuzzy linear optimization |
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. [UNESP] |
author_facet |
Castro, Evanize R. [UNESP] Saad, João C. C. [UNESP] Gabriel Filho, Luís R. A. [UNESP] |
author_role |
author |
author2 |
Saad, João C. C. [UNESP] Gabriel Filho, Luís R. A. [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Castro, Evanize R. [UNESP] Saad, João C. C. [UNESP] Gabriel Filho, Luís R. A. [UNESP] |
dc.subject.por.fl_str_mv |
decrease in annual costs Drip irrigation design flexibility restrictions fuzzy linear optimization |
topic |
decrease in annual costs Drip irrigation design flexibility restrictions fuzzy linear optimization |
description |
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 2023-03-01T20:03:26Z 2023-03-01T20:03:26Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1590/1809-4430-ENG.AGRIC.V42NEPE20210118/2022 Engenharia Agricola, v. 42, n. Special Issue, 2022. 1809-4430 0100-6916 http://hdl.handle.net/11449/240147 10.1590/1809-4430-ENG.AGRIC.V42NEPE20210118/2022 2-s2.0-85130855387 |
url |
http://dx.doi.org/10.1590/1809-4430-ENG.AGRIC.V42NEPE20210118/2022 http://hdl.handle.net/11449/240147 |
identifier_str_mv |
Engenharia Agricola, v. 42, n. Special Issue, 2022. 1809-4430 0100-6916 10.1590/1809-4430-ENG.AGRIC.V42NEPE20210118/2022 2-s2.0-85130855387 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Engenharia Agricola |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129594547503104 |