Construction of a Visual Platform for Higher Vocational Financial Education Combining Gaussian Hybrid Networks

Abstract

Abstract In this paper, a Gaussian mixture network distribution finance has been carried out to assess the risk, which is used as a risk assessment tool for the visual platform of higher vocational financial education. Financial data is quantified and determined by determining the cumulative expected loss amount to establish the financial investment risk assessment function. The Activiti open-source workflow engine was utilized to remove complex financial data and configure the K-line as the platform’s data visualization tool. Finally, the financial education visualization platform was used to analyze the Gaussian distribution and K-line data of X stock, which verified the practicality of the platform, and the effectiveness of the platform was verified by taking the students of H higher vocational college as the sample of the teaching experiment. The results show that the influence coefficient of the platform teaching on the quality of the course is 0.856, and the influence coefficient on the learning interest is 0.887, which indicates that the visual platform teaching makes students interested and strengthens their cognitive level. The visual digital reform of teaching finance majors in colleges and universities is provided with a new reference direction by this paper.