APPLICATION OF PROBABILISTIC SIMULATION AND BAYESIAN DECISION THEORY IN THE SELECTION OF MOLD REMEDIATION ACTIONS

摘要：

This paper utilizes a probabilistic mold risk assessment method, introducing a novel mold risk indicator (MRI). The MRI captures the risk of mold occurrence at identified “trouble spots under uncertainty. It will show how the MRI can enhance decision-making in a mold remediation case. When used in decision making under uncertainty, the MRI enables the best selection of remediation actions in the light of given preferences of the decision maker. In particular, decision makers are empowered to make a more rational decision based on a mold risk assessment that exceeds the usual deterministic performance evaluations. We will apply the Bayesian decision theory to the decision-making problem that involves the selection of two possible remediation actions in an existing building case. This approach demonstrates how to use additional information from mold simulation and uncertainty analysis in practical decision making problems and increasing the confidence of the decision maker.

关键词： Uncertainty analysis Mold risk assessment Bayesian decision theory Building simulation

作者: Hyeun Jun Moon Godfried Augenbroe

作者单位: Department of Architectural Engineering, College of Architecture, Dankook University, Seoul, 140-714 Doctoral Program, College of Architecture, Georgia Institute of Technology Atlanta, GA, 30332-0155,

会议类型: 国际会议

会议名称: 第10届建筑模拟国际会议

会议地点: 北京

会议语种:英文

在线出版日期: 2007-09-03（万方平台首次上网日期，不代表论文的发表时间）