Intelligent Evaluation System of Pathology Teaching Based on PSO Neural Network

Abstract

In order to improve the ability of intelligent diagnosis and evaluation of pathology
teaching, a design scheme of intelligent evaluation system of pathology teaching based on
PSO neural network is proposed. This paper constructs a sampling model of intelligent
assessment information in pathology teaching, analyzes the distribution characteristics of
big data in the intelligent evaluation system of pathology teaching, and adopts multi-mode
intelligent control method to design the stability control of intelligent evaluation system for
pathology teaching. The adaptive scheduling and learning algorithm design of intelligent
assessment of pathology teaching is carried out by using big data’s fusion scheduling
method. According to the interference information component of intelligent assessment of
pathology teaching, PSO neural network learning and equalization control are carried out.
The classification method of PSO neural network is used to realize the classification and
identification of various pathological diagnoses and the intelligent evaluation of pathology
teaching. The intelligent evaluation system of pathology teaching is developed in
embedded ARM and Linux environment. The system is divided into AD module,
information transmission module, intelligent control module and human-computer
interaction module. The test results show that the designed intelligent evaluation system of
pathology teaching has good human-computer interaction performance and the reliability
of the system is good