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Condition Rating Prediction Using An Interactive Deterioration Model Development Package, Minwoo Chang, Mitchell S. Maguire

Durham School of Architectural Engineering and Construction: Faculty Publications

This paper presents an advanced method to determine explanatory variables required for developing deterioration models without the interference of human bias. Although a stationary set of explanatory variables is ideal for long-term monitoring and asset management, the penalty regression results vary annually due to the innate bias in the inspection data. In this study, weighting factors were introduced to consider the inspection data collected for several years, and the most stationary set was identified. To manage the substantial amount of inspection data effectively, we proposed a software package referred to as the Deterioration Model Development Package (DMDP). The objective of …