TY - CONF
T1 - Development of classification model for the level of bid price volatility of public construction project focused on analysis of Pre-Bid clarification document
AU - Jang, Y. E.
AU - Yi, J. S.
AU - Son, J. W.
AU - Kang, H. B.
AU - Lee, J.
N1 - Funding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1D1A1A09083708).
Funding Information:
Also, this research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (No. NRF-2016R1A2B4015977).
Publisher Copyright:
© 2019 International Association for Automation and Robotics in Construction I.A.A.R.C. All rights reserved.
PY - 2019
Y1 - 2019
N2 - The purpose of this paper is to classify the level of formation of the bid price by using the type of uncertainty inherent in the bid document as a variable. To this end, the research examined the factors of the project related to the bid price presented in the previous study. Next, the pre-bid clarification document, which can be used to check the uncertainty of the bid documents, is used as a surrogate variable. Through these input variables, this research implemented two kinds of models using four algorithms: one predicts the level of bid price with uncertainty of bid document and the other predicts the level of bid price without uncertainty of bid documents. As a result, the model that predicts the level of the bid price reflecting the uncertainty of the bid document shows about 24 percent better performance than the model that predicts the bid price without reflecting the uncertainty of the bid document.
AB - The purpose of this paper is to classify the level of formation of the bid price by using the type of uncertainty inherent in the bid document as a variable. To this end, the research examined the factors of the project related to the bid price presented in the previous study. Next, the pre-bid clarification document, which can be used to check the uncertainty of the bid documents, is used as a surrogate variable. Through these input variables, this research implemented two kinds of models using four algorithms: one predicts the level of bid price with uncertainty of bid document and the other predicts the level of bid price without uncertainty of bid documents. As a result, the model that predicts the level of the bid price reflecting the uncertainty of the bid document shows about 24 percent better performance than the model that predicts the bid price without reflecting the uncertainty of the bid document.
KW - Bid Price Average
KW - Bid Price Range
KW - Bid Price Risk
KW - Bid Price Volatility
KW - Classification Model
KW - Machine Learning (ML)
KW - Pre-Bid Clarification
KW - Public Construction Project
KW - Risk Management
KW - Uncertainty of Bid Document
UR - http://www.scopus.com/inward/record.url?scp=85071435990&partnerID=8YFLogxK
M3 - Paper
AN - SCOPUS:85071435990
SP - 1245
EP - 1253
T2 - 36th International Symposium on Automation and Robotics in Construction, ISARC 2019
Y2 - 21 May 2019 through 24 May 2019
ER -