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• W1521130169 abstract "Construction productivity is constantly declining over a decade due to the lack of standardproductivity database system and the ignorance of impact of various factors influencing labor productivity.Prediction models developed earlier usually neglect the influencing factors which are subjective in nature suchas weather, site conditions etc. Many modeling techniques have been developed for predicting production ratesfor labor that incorporate the influence of various factors but artificial neural network (ANN) has been found tohave strong pattern recognition and learning capabilities to get reliable results. Therefore the objective of thisresearch is to develop a neural network prediction model for predicting labor production rates that takes intoaccount the factors which are in qualitative form. The objectives of the research have been achieved bycollecting production rates data for formwork of beams from different high rise concrete building structures bydirect observation. Reliable values of production rates have been successfully predicted by ANN. The averagevalue of 1.45xE-04 has been obtained for Mean Square Error (MSE) after testing the network . These resultsindicate that the ANN has predicted production rates values for beam formwork successfully with least range oferrors." @default.
• W1521130169 created "2016-06-24" @default.
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• W1521130169 date "2011-01-01" @default.
• W1521130169 modified "2023-09-26" @default.
• W1521130169 title "CONSTRUCTION LABOR PRODUCTION RATES MODELING USING ARTIFICIAL NEURAL NETWORK" @default.
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