Title :
Application of Fuzzy expert systems for construction labor productivity estimation
Author :
Muqeem, Sana ; Bin Idrus, Arazi ; Khamidi, Mohd Faris ; Siah, Yap Keem ; Saqib, Muhammad
Author_Institution :
Dept. of Civil Eng., Univ. Teknol. PETRONAS, Tronoh, Malaysia
Abstract :
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.
Keywords :
construction industry; expert systems; fuzzy reasoning; labour resources; least mean squares methods; production engineering computing; productivity; Likert scale; construction industry; construction labor productivity estimation; descriptive information; fuzzy expert systems; labor production rates; least root mean square error; linguistic accuracies; numerical accuracies; qualitative influential factors; quantitative influential factors; Accuracy; Expert systems; Fuzzy logic; Input variables; Pragmatics; Productivity; Artificial Intelligence; Fuzzy Expert Systems; Influencing Factors; Production rates;
Conference_Titel :
Computer & Information Science (ICCIS), 2012 International Conference on
Conference_Location :
Kuala Lumpeu
Print_ISBN :
978-1-4673-1937-9
DOI :
10.1109/ICCISci.2012.6297298