Study on the Application of Error Back-Propagation Algorithm Applied to the Student Status Management in Higher Education Institutions

Study on the Application of Error Back-Propagation Algorithm Applied to the Student Status Management in Higher Education Institutions

XinXiu Yang
DOI: 10.4018/IJICTE.348960
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Abstract

The objective of this work is to predict the employment rate of students based on the information in the SSM (student status management) in colleges and universities. Firstly, the relevant content of SSM is introduced. Secondly, the BP (Back Propagation) neural network, the LM (Levenberg Marquardt) algorithm, and the BR (Bayesian Regularization) algorithm are introduced. In addition, the LM algorithm is combined with the BR algorithm to optimize the BP neural network, so as to establish a prediction model of the employment rate of college graduates based on the LM-BP neural network (the established prediction model). Finally, the established prediction model is verified after the historical data of college students in the SSM are managed and processed using the big data analysis technology. It suggests that the established prediction model shows higher prediction accuracy, more stable prediction performance, more ideal prediction effect, and higher practical application value.
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Materials And Methods

SSM in Colleges and Universities

The SSM can be defined extensively and narrowly. In a broad sense, SSM refers to a series of activities such as records and assessments that are included in the student's admission, school study, and one-page process. SSM refers to a card that records student status information in the narrow sense. Student status management is a very important part of the student management process. In the process of SSM in the traditional mode, the amount of student status information is relatively large, and it is also relatively difficult for staff to manage manually (Shi, 2021). The general business of SSM is shown in Figure 1. Generally, it includes the business of student status change, reward and punishment management business, data query and statistics business, student status registration management business, student graduation management business, and student status filing management business.

Figure 1.

Business of SSM

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The overall process of the SSM system is shown in Figure 2. In the process of development, colleges and universities must comprehensively strengthen college management. Many shortcomings of traditional colleges and universities can be solved by using the SSM information system. Student status management provides very important content in the process of university management. Through SSM, the graduation information of students can be integrated, and the employment rate of students can be predicted, which helps colleges and graduates to achieve accurate employment and professional positioning and effectively evaluate their own abilities (Ding et al., 2019).

Figure 2.

The overall process of the student status information management system

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