A Big Data Approach for Investigating Bridge Deterioration and Maintenance Strategies in Taiwan

Due to the dwindling maintenance budget and lack of qualified bridge inspectors, bridge-management agencies in Taiwan need develop cost-effective inspection strategies preserve safety functionality their aging, natural disaster-prone bridges. To inform development such a strategy, this study examined big data stored Bridge Management System (TBMS) using knowledge discovery databases (KDD) process. Cluster association algorithms were applied inventory five-year 2849 bridges determine structural configurations components that are prone deterioration. can use results presented reevaluate current concentrate limited resources on most