![]() Particularly, the sample group consisted of 136 units of residences, commercial buildings, and common housing buildings. Meanwhile, the representatives of any sample groups were selected by randomization comprising 14, 15, and 15 units respectively. ![]() On this matter, the researcher assigned the experimental group as the representative to simulate the multiple regression equation model and the artificial neural network model comprising 30, 32, and 30 units respectively. The researcher conducted this study with the aims to: 1) investigate the effective factors toward the construction workload prediction 2) compare the effectiveness between a multiple regression model and an artificial neural networks model 3) describe the relationship amongst the construction materials. Pricing management is a key mechanism for the cost control before starting any project while the ability to validate the quantity take-off can be a method to increase the effectiveness for the construction workload accounting.
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