A target drug addict relapse probability analysis model is disclosed. A relapse inducement event set is constructed by collecting inducement events possibly causing relapse of a drug addict, and a relapse probability initial analysis model is established through a Bayesian network and a joint tree reasoning algorithm on the basis of the relapse inducement event set; and preferably, a new relapse incentive event set can be introduced to the Bayesian neural network for multiple times to obtain a corrected posterior probability, the prior probability in the initial relapse probability analysis model is corrected, and a relapse probability correction analysis model is established. According to the model, a supervisor can be helped to predict the relapse behavior of the target drug addict, and meanwhile, high and low relevance incentive events causing the relapse behavior can be judged from the relapse incentive event set of the target drug addict, so that the supervisor can reasonably pay attention to the incentive events.
Target drug addict relapse probability analysis model