Analysis of Multiinterface Autonomous Moral Learning Platform Based on Intelligent Computing

Abstract

In order to realize the self-learning of the platform, an improved RBF neural network model is adopted, and a similarity matching algorithm is added, which improves the comfort of platform users and reduces redundant knowledge links. Based on constructivism, platform moral education constructs an intelligent computing learning platform with autonomous learning function through the construction mode. Based on the relatively perfect database, the moral learning platform extracts relevant resources for the platform teaching mode and basic services respectively, so as to optimize the platform design. Rely on computer technology to establish educational resource database, extract or collect teaching resources from all aspects, and form a database group with complete information. After the platform content design is completed, different interfaces are used to link to different end users. The establishment of multi-interface can make the system online at different terminals, fully consider the user’s moral learning environment, and let users learn online anytime and anywhere. Compared with the traditional algorithm, the improved algorithm adds the similar matching function on the basis of RBF algorithm. It reduces the phenomenon of repeated push in students’ autonomous learning system. The similarity matching algorithm is added to improve the comfort of platform users and reduce the redundant knowledge chain. The construction of moral learning teaching mode not only increases the interaction of the platform, but also improves the efficiency of user education and learning, and enhances the user’s awareness of intelligent computing.