Bayesian Model for Cost Estimation of Construction Projects

Title
Bayesian Model for Cost Estimation of Construction Projects
Author(s)
김상용
Keywords
Bayesian; Cost estimating; Markov Chain Monte Carlo
Issue Date
201102
Publisher
한국건축시공학회
Citation
한국건축시공학회지, v.11, no.1, pp.91 - 99
Abstract
Bayesian network is a form of probabilistic graphical model. It incorporates human reasoning to deal with sparse data availability and to determine the probabilities of uncertain cases. In this research, bayesian network is adopted to model the problem of construction project cost. General information, time, cost, and material, the four main factors dominating the characteristic of construction costs, are incorporated into the model. This research presents verify a model that were conducted to illustrate the functionality and application of a decision support system for predicting the costs. The Markov Chain Monte Carlo (MCMC) method is applied to estimate parameter distributions. Furthermore, it is shown that not all the parameters are normally distributed. In addition, cost estimates based on the Gibbs output is performed. It can enhance the decision the decision-making process.
URI
http://hdl.handle.net/YU.REPOSITORY/25627
ISSN
1598-2033
Appears in Collections:
건축학부 > 건축학부 > Articles
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