Application of Fuzzy expert systems for construction labor productivity estimation

Fuzzy Expert Systems have been used to solve complex problems efficiently in the case where information available is in descriptive form rather than quantitative number. This study has aimed to use Fuzzy expert systems to estimate the labor production rates through incorporating the influence of qua...

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Main Authors: Muqeem S., Bin Idrus A., Khamidi M.F., Siah Y.K., Saqib M.
Other Authors: 42561828800
Format: Conference Paper
Published: 2023
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-303092024-04-17T10:38:15Z Application of Fuzzy expert systems for construction labor productivity estimation Muqeem S. Bin Idrus A. Khamidi M.F. Siah Y.K. Saqib M. 42561828800 26532953200 27567869500 24448864400 55620498500 Artificial Intelligence Fuzzy Expert Systems Influencing Factors Production rates Artificial intelligence Construction industry Information science Mean square error Productivity Surveys Technology Complex problems Fuzzy expert systems Influencing factor Influential factors Labor productivity Numerical accuracy Production rates Productivity estimation Quantitative factors Questionnaire surveys Root mean square errors Expert systems Fuzzy Expert Systems have been used to solve complex problems efficiently in the case where information available is in descriptive form rather than quantitative number. This study has aimed to use Fuzzy expert systems to estimate the labor production rates through incorporating the influence of qualitative and quantitative factor. Production rate values of concreting of columns and their influential factors have been collected from questionnaire survey. Overall ten influential factors of qualitative and quantitative nature are selected for collecting the data during questionnaire survey based on the Likert scale of 1 to 5. Fuzzy expert system developed in this study has been compared with the two previously used Fuzzy expert systems for productivity estimation. Performance of the previous systems and system developed in this study has been compared by calculating Root Mean Square Error. The findings revealed that system developed in the study gives high linguistic and numerical accuracies as compare to the previous systems with least Root Mean Square Error. Hence, the developed Fuzzy expert system can be used reliably for estimating labor productivity by the construction Industry. � 2012 IEEE. Final 2023-12-29T07:46:33Z 2023-12-29T07:46:33Z 2012 Conference Paper 10.1109/ICCISci.2012.6297298 2-s2.0-84867916944 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867916944&doi=10.1109%2fICCISci.2012.6297298&partnerID=40&md5=4dd790e7c49777c2cb21e1d4b5b15258 https://irepository.uniten.edu.my/handle/123456789/30309 1 6297298 506 511 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Artificial Intelligence
Fuzzy Expert Systems
Influencing Factors
Production rates
Artificial intelligence
Construction industry
Information science
Mean square error
Productivity
Surveys
Technology
Complex problems
Fuzzy expert systems
Influencing factor
Influential factors
Labor productivity
Numerical accuracy
Production rates
Productivity estimation
Quantitative factors
Questionnaire surveys
Root mean square errors
Expert systems
spellingShingle Artificial Intelligence
Fuzzy Expert Systems
Influencing Factors
Production rates
Artificial intelligence
Construction industry
Information science
Mean square error
Productivity
Surveys
Technology
Complex problems
Fuzzy expert systems
Influencing factor
Influential factors
Labor productivity
Numerical accuracy
Production rates
Productivity estimation
Quantitative factors
Questionnaire surveys
Root mean square errors
Expert systems
Muqeem S.
Bin Idrus A.
Khamidi M.F.
Siah Y.K.
Saqib M.
Application of Fuzzy expert systems for construction labor productivity estimation
description Fuzzy Expert Systems have been used to solve complex problems efficiently in the case where information available is in descriptive form rather than quantitative number. This study has aimed to use Fuzzy expert systems to estimate the labor production rates through incorporating the influence of qualitative and quantitative factor. Production rate values of concreting of columns and their influential factors have been collected from questionnaire survey. Overall ten influential factors of qualitative and quantitative nature are selected for collecting the data during questionnaire survey based on the Likert scale of 1 to 5. Fuzzy expert system developed in this study has been compared with the two previously used Fuzzy expert systems for productivity estimation. Performance of the previous systems and system developed in this study has been compared by calculating Root Mean Square Error. The findings revealed that system developed in the study gives high linguistic and numerical accuracies as compare to the previous systems with least Root Mean Square Error. Hence, the developed Fuzzy expert system can be used reliably for estimating labor productivity by the construction Industry. � 2012 IEEE.
author2 42561828800
author_facet 42561828800
Muqeem S.
Bin Idrus A.
Khamidi M.F.
Siah Y.K.
Saqib M.
format Conference Paper
author Muqeem S.
Bin Idrus A.
Khamidi M.F.
Siah Y.K.
Saqib M.
author_sort Muqeem S.
title Application of Fuzzy expert systems for construction labor productivity estimation
title_short Application of Fuzzy expert systems for construction labor productivity estimation
title_full Application of Fuzzy expert systems for construction labor productivity estimation
title_fullStr Application of Fuzzy expert systems for construction labor productivity estimation
title_full_unstemmed Application of Fuzzy expert systems for construction labor productivity estimation
title_sort application of fuzzy expert systems for construction labor productivity estimation
publishDate 2023
_version_ 1806426145850130432