Competency Evaluation of Rail Transport Drivers Based on Bayesian Networks

We obtained the competency evaluation indicators of rail transport drivers according to the survey analysis,and the indicators included 4 first-level evaluation indicators and 16 second-level evaluation indicators.To regard these indicators as variables,and based on the principles of Bayesian networks,the competence Bayesian networks of rail transport drivers were built.We chose vocational psychology characteristics and vocational theory characteristics as the intermediate nodes,the extent of mastering the rules and regulations,level of vehicle theoretical knowledge,learning ability and complexity response ability as father node,competency of rail transport drivers as child node,and then we built the simplified sub-Bayesian network of rail transport drivers' competency.Through analyzing the example by this sub-Bayesian network,the results show that vocational psychology characteristics play a more important role in the competence of rail transport drivers.The evaluation results can accurately reflect the interactions among all the evaluation indicators for the competence of rail transport drivers.The method can provide a quantitative analysis basis for rail transport drivers' selection,training and retirement.