ESTIMATING CONSTRUCTION LABOR PRODUCTIVITY FOR CONCRETING ACTIVITY USING ARTIFICIAL NEURAL NETWORK

摘要

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.