A resource management method based on organizational behavior theory and hidden Markov algorithm

In order to improve the level of human resource management in modern enterprises, a human resource management method in modern enterprises based on organizational behavior theory and hidden Markov algorithm is proposed. First of all, according to characteristics of human resources training, human resources are analyzed from the aspects of psychological capital and incentive theory in the organizational behavior theory to maximize the advantages of human resources, which is of great significance. Secondly, targeted at data partitioning and unknown model quantities in discovery process of the hidden model, the hidden Markov algorithm using Dirichlet process and non-parametric bayesian factors are analyzed for data flow partitioning of human resource management in modern enterprises and model discovery; with psychological capital and incentive theory in organizational behavior theory as the starting point, role of organizational behavior theory in human resources training is explored in this Thesis.