@article{Prapaporn_2019, place={Phitsanulok, Thailand}, title={An analysis on material quantity relationship of reinforced concrete buildings between Multiple Linear Regression and Artificial Neural Network}, volume={14}, url={https://ph01.tci-thaijo.org/index.php/nuej/article/view/141406}, abstractNote={<p>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. 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. 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. Meanwhile, the representatives of any sample groups were selected by randomization comprising 14, 15, and 15 units respectively. Particularly, the sample group consisted of 136 units of residences, commercial buildings, and common housing buildings. Based on the study, it could be described that the independent variables as 1) the average area per floor and 2) Number of floors represents the significantly description of the dependent variable were: 1) Concrete Work; 2) Reinforced Steel Work; 3) Formwork; and 4) Precast Concrete Slabs; meanwhile, the architectural work consisted of: 1) Floor Material ; 2) Manasory work ; 3) Ceiling Material; and 4) Door and Window Material. Besides, the artificial neural network model could describe changes of the construction material quantity with more accurate result than did the multiple regression model. This study also noted that the works of each sample group were significantly different from one another; Namely, 1) A mutual relationship between Concrete quantity (m<sup>3</sup>) per Construction area (m<sup>2</sup>) was confirmed as 0.27, 0.195, and 0.168; 2) A mutual relationship between Reinforced steel (kg) per Concrete (m<sup>3</sup>) was confirmed as 85.44, 118.235, and 113.49; 3) A mutual relationship between Formwork (m<sup>2</sup>) per Concrete (m<sup>3</sup>) was confirmed as 9.46, 9.20, and 9.24 4; 4) A mutual relationship between Manasory work (m<sup>2</sup>) per Construction area (m<sup>2</sup>) was confirmed as 0.32, 1.62, and 1.33; and 5) A mutual relationship between Door and Window (m<sup>2</sup>) per Manasory work (m<sup>2</sup>) was confirmed as 0.12, 0.13, and 0.15. These data were the results found from the case studies on the residences, commercial buildings, and common housing buildings respectively.</p>}, number={1}, journal={Naresuan University Engineering Journal}, author={Prapaporn, Wantana}, year={2019}, month={Jun.}, pages={84–102} }