Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil
Autor(a) principal: | |
---|---|
Data de Publicação: | 2017 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Independent Journal of Management & Production |
Texto Completo: | http://www.ijmp.jor.br/index.php/ijmp/article/view/645 |
Resumo: | This study involves an assessment of various artificial intelligence-related techniques which aim to produce a more robust system for sediment transport modeling. The intelligent systems developed in this research are directly applicable to academic knowledge and use data from a report on "water circulation assessment in the “Linguado” Channel and Babitonga Bay ,”Santa Catarina”, Brazil, developed by Military Engineering Institute (IME). The solution employed for sediment transport was built using an intelligent system from the conception of two hybrid models. The first was a Neuro-Fuzzy (ANFIS) hybrid model for the study of hydrodynamic behavior, aiming to determine flow rate in the channel. The second was a fuzzy genetic model, able to assess sediment transport in the “Linguado” Channel. The study's conclusion compares the different effects involved in the dredging equilibrium in the “Linguado” Channel according to this hybrid model with the results obtained using a finite element model in the MIKE21® software. |
id |
IJMP_115cf589369c1f93a4df96cfa194e9bf |
---|---|
oai_identifier_str |
oai:www.ijmp.jor.br:article/645 |
network_acronym_str |
IJMP |
network_name_str |
Independent Journal of Management & Production |
repository_id_str |
|
spelling |
Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazilhydrodynamicssediment transportfuzzy logicgenetic algorithmneural networkANFISThis study involves an assessment of various artificial intelligence-related techniques which aim to produce a more robust system for sediment transport modeling. The intelligent systems developed in this research are directly applicable to academic knowledge and use data from a report on "water circulation assessment in the “Linguado” Channel and Babitonga Bay ,”Santa Catarina”, Brazil, developed by Military Engineering Institute (IME). The solution employed for sediment transport was built using an intelligent system from the conception of two hybrid models. The first was a Neuro-Fuzzy (ANFIS) hybrid model for the study of hydrodynamic behavior, aiming to determine flow rate in the channel. The second was a fuzzy genetic model, able to assess sediment transport in the “Linguado” Channel. The study's conclusion compares the different effects involved in the dredging equilibrium in the “Linguado” Channel according to this hybrid model with the results obtained using a finite element model in the MIKE21® software.Independent2017-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlhttp://www.ijmp.jor.br/index.php/ijmp/article/view/64510.14807/ijmp.v8i4.645Independent Journal of Management & Production; Vol. 8 No. 4 (2017): Independent Journal of Management & Production; 1210-12222236-269X2236-269Xreponame:Independent Journal of Management & Productioninstname:Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)instacron:IJM&Penghttp://www.ijmp.jor.br/index.php/ijmp/article/view/645/756http://www.ijmp.jor.br/index.php/ijmp/article/view/645/790Copyright (c) 2017 Edison Conde Perez dos Santos, Carlos Alberto Nunes Cosenza, José Carlos Cesar Amoriminfo:eu-repo/semantics/openAccessSantos, Edison Conde Perez dosCosenza, Carlos Alberto NunesAmorim, José Carlos Cesar2018-09-04T13:00:48Zoai:www.ijmp.jor.br:article/645Revistahttp://www.ijmp.jor.br/PUBhttp://www.ijmp.jor.br/index.php/ijmp/oaiijmp@ijmp.jor.br||paulo@paulorodrigues.pro.br||2236-269X2236-269Xopendoar:2018-09-04T13:00:48Independent Journal of Management & Production - Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)false |
dc.title.none.fl_str_mv |
Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil |
title |
Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil |
spellingShingle |
Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil Santos, Edison Conde Perez dos hydrodynamics sediment transport fuzzy logic genetic algorithm neural network ANFIS |
title_short |
Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil |
title_full |
Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil |
title_fullStr |
Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil |
title_full_unstemmed |
Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil |
title_sort |
Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil |
author |
Santos, Edison Conde Perez dos |
author_facet |
Santos, Edison Conde Perez dos Cosenza, Carlos Alberto Nunes Amorim, José Carlos Cesar |
author_role |
author |
author2 |
Cosenza, Carlos Alberto Nunes Amorim, José Carlos Cesar |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Santos, Edison Conde Perez dos Cosenza, Carlos Alberto Nunes Amorim, José Carlos Cesar |
dc.subject.por.fl_str_mv |
hydrodynamics sediment transport fuzzy logic genetic algorithm neural network ANFIS |
topic |
hydrodynamics sediment transport fuzzy logic genetic algorithm neural network ANFIS |
description |
This study involves an assessment of various artificial intelligence-related techniques which aim to produce a more robust system for sediment transport modeling. The intelligent systems developed in this research are directly applicable to academic knowledge and use data from a report on "water circulation assessment in the “Linguado” Channel and Babitonga Bay ,”Santa Catarina”, Brazil, developed by Military Engineering Institute (IME). The solution employed for sediment transport was built using an intelligent system from the conception of two hybrid models. The first was a Neuro-Fuzzy (ANFIS) hybrid model for the study of hydrodynamic behavior, aiming to determine flow rate in the channel. The second was a fuzzy genetic model, able to assess sediment transport in the “Linguado” Channel. The study's conclusion compares the different effects involved in the dredging equilibrium in the “Linguado” Channel according to this hybrid model with the results obtained using a finite element model in the MIKE21® software. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-12-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.ijmp.jor.br/index.php/ijmp/article/view/645 10.14807/ijmp.v8i4.645 |
url |
http://www.ijmp.jor.br/index.php/ijmp/article/view/645 |
identifier_str_mv |
10.14807/ijmp.v8i4.645 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.ijmp.jor.br/index.php/ijmp/article/view/645/756 http://www.ijmp.jor.br/index.php/ijmp/article/view/645/790 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf text/html |
dc.publisher.none.fl_str_mv |
Independent |
publisher.none.fl_str_mv |
Independent |
dc.source.none.fl_str_mv |
Independent Journal of Management & Production; Vol. 8 No. 4 (2017): Independent Journal of Management & Production; 1210-1222 2236-269X 2236-269X reponame:Independent Journal of Management & Production instname:Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP) instacron:IJM&P |
instname_str |
Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP) |
instacron_str |
IJM&P |
institution |
IJM&P |
reponame_str |
Independent Journal of Management & Production |
collection |
Independent Journal of Management & Production |
repository.name.fl_str_mv |
Independent Journal of Management & Production - Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP) |
repository.mail.fl_str_mv |
ijmp@ijmp.jor.br||paulo@paulorodrigues.pro.br|| |
_version_ |
1797220491394547712 |