Construction duration predictive model based on factorial analysis and fuzzy logic
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Ambiente construído (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-86212019000400115 |
Resumo: | Abstract Setting the building construction duration for vertical residential works is made still in the study phase of economic and financial feasibility of the project and, in most cases, in an empirical way, increasing the uncertainties and the risks to fulfill the set deadline. However, there are computational intelligence tools that can contribute to reduce the degree of uncertainty. This study aimed to investigate the use of a hybrid system to estimate the deadline for vertical residential building works from design and production characteristics using factorial analysis and Fuzzy Systems. To this end, we used information of a database from the SEURB and in some buildings construction companies in Belém, a city located in the State of Pará, northern of Brazil. For the training and construction of the Fuzzy Forecast Model, data from 71 projects were used and 16 others residential buildings were used for its validation. The results showed a significant level of assertiveness, with 75% accuracy considering a range, whose upper and lower limits were calculated from MAPE and MASE. The model presented a prediction performance superior to other models already consecrated in the literature. |
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Ambiente construído (Online) |
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Construction duration predictive model based on factorial analysis and fuzzy logicFuzzy modeling systemsFuzzy systemsBuilding constructionDeadlineAbstract Setting the building construction duration for vertical residential works is made still in the study phase of economic and financial feasibility of the project and, in most cases, in an empirical way, increasing the uncertainties and the risks to fulfill the set deadline. However, there are computational intelligence tools that can contribute to reduce the degree of uncertainty. This study aimed to investigate the use of a hybrid system to estimate the deadline for vertical residential building works from design and production characteristics using factorial analysis and Fuzzy Systems. To this end, we used information of a database from the SEURB and in some buildings construction companies in Belém, a city located in the State of Pará, northern of Brazil. For the training and construction of the Fuzzy Forecast Model, data from 71 projects were used and 16 others residential buildings were used for its validation. The results showed a significant level of assertiveness, with 75% accuracy considering a range, whose upper and lower limits were calculated from MAPE and MASE. The model presented a prediction performance superior to other models already consecrated in the literature.Associação Nacional de Tecnologia do Ambiente Construído - ANTAC2019-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-86212019000400115Ambiente Construído v.19 n.4 2019reponame:Ambiente construído (Online)instname:Associação Nacional de Tecnologia do Ambiente Construído (ANTAC)instacron:ANTAC10.1590/s1678-86212019000400346info:eu-repo/semantics/openAccessMaués,Luiz Maurício FurtadoSá,José Alberto Silva deCosta Junior,Carlos Tavares daKern,Andrea PariseDuarte,André Augusto Azevedo Montenegroeng2020-05-05T00:00:00Zoai:scielo:S1678-86212019000400115Revistahttps://seer.ufrgs.br/ambienteconstruidohttps://old.scielo.br/oai/scielo-oai.php||ambienteconstruido@ufrgs.br1678-86211415-8876opendoar:2020-05-05T00:00Ambiente construído (Online) - Associação Nacional de Tecnologia do Ambiente Construído (ANTAC)false |
dc.title.none.fl_str_mv |
Construction duration predictive model based on factorial analysis and fuzzy logic |
title |
Construction duration predictive model based on factorial analysis and fuzzy logic |
spellingShingle |
Construction duration predictive model based on factorial analysis and fuzzy logic Maués,Luiz Maurício Furtado Fuzzy modeling systems Fuzzy systems Building construction Deadline |
title_short |
Construction duration predictive model based on factorial analysis and fuzzy logic |
title_full |
Construction duration predictive model based on factorial analysis and fuzzy logic |
title_fullStr |
Construction duration predictive model based on factorial analysis and fuzzy logic |
title_full_unstemmed |
Construction duration predictive model based on factorial analysis and fuzzy logic |
title_sort |
Construction duration predictive model based on factorial analysis and fuzzy logic |
author |
Maués,Luiz Maurício Furtado |
author_facet |
Maués,Luiz Maurício Furtado Sá,José Alberto Silva de Costa Junior,Carlos Tavares da Kern,Andrea Parise Duarte,André Augusto Azevedo Montenegro |
author_role |
author |
author2 |
Sá,José Alberto Silva de Costa Junior,Carlos Tavares da Kern,Andrea Parise Duarte,André Augusto Azevedo Montenegro |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Maués,Luiz Maurício Furtado Sá,José Alberto Silva de Costa Junior,Carlos Tavares da Kern,Andrea Parise Duarte,André Augusto Azevedo Montenegro |
dc.subject.por.fl_str_mv |
Fuzzy modeling systems Fuzzy systems Building construction Deadline |
topic |
Fuzzy modeling systems Fuzzy systems Building construction Deadline |
description |
Abstract Setting the building construction duration for vertical residential works is made still in the study phase of economic and financial feasibility of the project and, in most cases, in an empirical way, increasing the uncertainties and the risks to fulfill the set deadline. However, there are computational intelligence tools that can contribute to reduce the degree of uncertainty. This study aimed to investigate the use of a hybrid system to estimate the deadline for vertical residential building works from design and production characteristics using factorial analysis and Fuzzy Systems. To this end, we used information of a database from the SEURB and in some buildings construction companies in Belém, a city located in the State of Pará, northern of Brazil. For the training and construction of the Fuzzy Forecast Model, data from 71 projects were used and 16 others residential buildings were used for its validation. The results showed a significant level of assertiveness, with 75% accuracy considering a range, whose upper and lower limits were calculated from MAPE and MASE. The model presented a prediction performance superior to other models already consecrated in the literature. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-12-01 |
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=S1678-86212019000400115 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-86212019000400115 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/s1678-86212019000400346 |
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 Nacional de Tecnologia do Ambiente Construído - ANTAC |
publisher.none.fl_str_mv |
Associação Nacional de Tecnologia do Ambiente Construído - ANTAC |
dc.source.none.fl_str_mv |
Ambiente Construído v.19 n.4 2019 reponame:Ambiente construído (Online) instname:Associação Nacional de Tecnologia do Ambiente Construído (ANTAC) instacron:ANTAC |
instname_str |
Associação Nacional de Tecnologia do Ambiente Construído (ANTAC) |
instacron_str |
ANTAC |
institution |
ANTAC |
reponame_str |
Ambiente construído (Online) |
collection |
Ambiente construído (Online) |
repository.name.fl_str_mv |
Ambiente construído (Online) - Associação Nacional de Tecnologia do Ambiente Construído (ANTAC) |
repository.mail.fl_str_mv |
||ambienteconstruido@ufrgs.br |
_version_ |
1754209104382918656 |