Estimating Productivity of Brickwork item using Logistic and Multiple Regression Approaches

Journal Title: Scholars Journal of Engineering and Technology - Year 2016, Vol 4, Issue 5

Abstract

Abstract:Regression analysis of the most common techniques in estimating labor productivity rates in Iraqi construction projects. In the first part of this research has been identified the factors and variables are affecting to the brickwork productivity and most important of these variables the age, experience, high building, the number of workers and security condition of the site. One model was built for the prediction the labor productivity rates for brickwork item. The data used in this model was collected from construction project in Iraq. It was found that Multiple Linear Regression (MLR) have the ability to predict the construction productivity for brickworks with a good degree of accuracy of the coefficient of correlation (R) was 87.28%,and average accuracy percentage of 92.5%.In the second part of this research was development another mathematical model for the same variables using Logistic Regression Technique (LRT). Results of the study showed that the use of a binary logistic regression gave a logical response results are consistent with the studied casewith a moderate degree of average accuracy percentage of 95.8%.the application of Logistic Regression Technique, as a modern technique, in Iraqi construction project is necessary to ensure successful management, and many of the planners feel the need of such system in planning stage of construction project. Based on the foregoing, the study recommends expanding the use of logistic regression to estimate productivity. Keywords:Multiple Linear Regression, Logistic Regression Technique, labor productivity rates.

Authors and Affiliations

Saja H Rasool, Faiq M. S. Al Zwainy

Keywords

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  • EP ID EP385447
  • DOI -
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How To Cite

Saja H Rasool, Faiq M. S. Al Zwainy (2016). Estimating Productivity of Brickwork item using Logistic and Multiple Regression Approaches. Scholars Journal of Engineering and Technology, 4(5), 234-243. https://europub.co.uk/articles/-A-385447