Managing risk in civil engineering by machine learning from failures

Many failures which occur in engineering can be shown to have developed though similar patterns. Machine learning using discrimination and connectivity can be used to determine these common patterns of events, and hence to build a knowledge base against which new projects may be compared. Support logic measures of uncertainty are associated with the knowledge-base concepts, and a measure of similarity is introduced.<>