The effective model of transformation of ideological and political education in universities based on artificial intelligence

Abstract

In the context of artificial intelligence, the path of knowledge transmission needs to be transformed. In essence, the transmission of knowledge and the transformation of information transmission methods are integrated. This paper studies the foreign object tracking algorithm, analyzes the error in the target tracking algorithm, and uses the BP neural network principle to modify the IMM algorithm. Aiming at the problem of low tracking accuracy when the target is maneuvering, this paper analyzes the linearization error of Kalman filter and builds a BP neural network to correct the tracking model of IMM. The model creates a target prediction training set and a test set, optimizes the parameters of the neural network, and conducts simulation experiments using MATLAB, which proved that the model had a higher accuracy in predicting the target trajectory of foreign objects. Therefore, the transformation of ideological and political teaching mode in colleges and universities can be realized, and the intelligent classroom of ideological and political education and intelligent communication have technical support.