This paper proposes a new fusion neural network (FC) based on attribute hierarchy (AHM). This paper studies the evolution model of ideological and political subjects based on this method. It is abbreviated as the AHM-FC model with unequal weighted features. Then, based on the Bayesian network and least squares feature hierarchy analysis, this paper gives the conditional probability and attribute weight of ideological and political subjects. Furthermore, this paper establishes the theme evolution model of “double fusion and three stages.” In this way, it has been fully applied in ideological and political teaching in colleges and universities. Experimental results show that FC-AHM based on unequal weights can predict the evolution of ideological and political objects with higher accuracy.