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Transportation Technology Center Inc (TTCI) conducts neural network analysis for rail flaw prediction

Transportation Technology Center Inc (TTCI) conducts neural network analysis for rail flaw prediction

03 May 2019

TTCI investigated using a neural network technique to predict bolt hole crack, vertical split head, and crushed head rail flaws. The neural network model was developed to capture existing non-linear relationships between input variables pertaining to rail flaw development and rail defect outputs. Training and validation data were combined into three distinct groups (autumn/spring, summer, and winter) and models were developed for each defect type and group.

R T & S: Railway Track and Structures, April 2019, pp.9-12

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