Data Mining of Bridge Concrete Deck Parameters in the National Bridge Inventory by Two-Step Cluster Analysis

Abstract

AbstractData mining is a discovery procedure to explore and visualize useful but less-than-obvious information or patterns in large collections of data. Given the amount and varying parameter types in a large data set such as that of the National Bridge Inventory (NBI), using traditional clustering techniques for discovery is impractical. As a consequence, the authors have applied a novel data discovery tool, called Two-step cluster analysis, to visualize associations between concrete bridge deck design parameters and bridge deck condition ratings. Two-step cluster analysis is a powerful knowledge discovery tool that can handle categorical and interval data simultaneously and is capable of reducing dimensions for large data sets. The analysis, of a total of 9,809 concrete highway bridge decks in the Northeast climatic region, found that bridges with cast-in-place decks that have a bituminous wearing surface, a preformed fabric membrane, and epoxy-coated reinforcement protection are strongly associated wit...