Estimating construction labor productivity for concreting activity using artificial neural network

Arazi Idrus, Sana Muqeem, Mohd Faris Khamidi, M. Saiful Bin Zakariya

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Due to insufficient standard productivity measurement system, the Construction labor productivity has been declining over a decade. In addition, the influences of various qualitative factors on labor productivity have not been incorporated accurately during the scheduling and estimation of the project durations. Therefore the objective of the study is to estimate the labor production rates by using Artificial Neural Network (ANN). Qualitative factors influencing the rates such as weather, project location, site conditions, etc. have been identified on project sites during the measurement of production rates values for concreting activities. Data obtained from seven building project sites have been used in the ANN for estimating labor production rates. The results obtained with the least error can be used as reliable and valid production rates for the Malaysian construction industry.

    Original languageEnglish
    Title of host publicationProceedings of the 2011 International Conference on Computer and Computational Intelligence, December 2-3, 2011, Bangkok, Thailand
    EditorsYi Xie
    PublisherAmerican Society of Mechanical Engineers
    Pages507-511
    Number of pages5
    ISBN (Print)9780791859926
    DOIs
    Publication statusPublished - 2011
    EventInternational Conference on Computer and Computational Intelligence - Bangkok, Thailand
    Duration: 2 Dec 20113 Dec 2011

    Conference

    ConferenceInternational Conference on Computer and Computational Intelligence
    Abbreviated titleICCCI 2011
    CountryThailand
    CityBangkok
    Period2/12/113/12/11

    Keywords

    • Production rates
    • Influencing factors
    • Artificial Neural Networks

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