Journal Title : International Journal of Modern Trends in Engineering and Science


Author’s Name : T Aswin Dayanand | S Shanmugapriya  unnamed

Volume 03 Issue 08 2016

ISSN no:  2348-3121

Page no: 231-238

Abstract – Various models have been developed for the estimation of labor productivity but they do not provide reliable and accurate results, because of lack of valid and reliable information on production rates. Currently, production rates data is taken from the historical record, personal opinions and judgments. Therefore, the objective of this study is to develop an estimation model for construction labor productivity that provides reliable production rates that also takes into account of the factors influencing productivity by using Artificial Neural Network (ANN). The impact of different factors on construction productivity can be quantified by productivity models. Modeling of construction labour productivity could be challenging when effects of multiple factors are considered simultaneously. In this study the multiple factors affecting the productivity are used as an input for developing productivity model using Artificial Neural Network (ANN) method. Finally, a new data set is used in ANN to develop an estimation model. The Predicted Rate from the model is compared with Actual rate and difference is found. From the difference Mean Squared Error (MSE) is found. These models play an important role in construction estimating, Scheduling, and planning decisions.

Keywords— Artificial Neural Network (ANN), production rates, influencing factors 


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