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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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 |
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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 |
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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 |
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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. |
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42561828800 |
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42561828800 Muqeem S. Bin Idrus A. Khamidi M.F. Siah Y.K. Saqib M. |
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Conference Paper |
author |
Muqeem S. Bin Idrus A. Khamidi M.F. Siah Y.K. Saqib M. |
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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 |
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2023 |
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1806426145850130432 |