Identification of Poverty in College Students Using Campus Dining Consumption Data: An Elman Neural Network Approach

DOI

10.2991/978-94-6463-417-4_13How to use a DOI?

Keywords

Principal Components Analysis; Triple classification; Elman; Prediction; Identification of needy students

Abstract

In recent years, China’s colleges and universities have launched the “poor college student aid” programme, which aims to provide scholarships for students who are unable to attend school due to family difficulties. Therefore, how to accurately identify students with financial difficulties in colleges and universities is of great significance to the financial aid work of colleges and universities. The purpose of this paper is to study the identification of poor students based on restaurant consumption data, with the aim of providing a more scientific and accurate method for efficient financial aid work, so as to improve the quality and social fairness of higher education. This paper uses data mining theories, such as K-means clustering analysis algorithm and Elman neural network prediction model, combined with the information provided by a university, such as the amount and number of students’ consumption throughout the day for three years, to study the method of identifying poor students from the perspective of big data. Based on the final calculation of the F1 values, it can be concluded that all F1 values exceed 98%. This indicates that the model’s results are highly accurate and would effectively assist students in need.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Wenhui Li
AU  - Yiming Wang
PY  - 2024
DA  - 2024/05/07
TI  - Identification of Poverty in College Students Using Campus Dining Consumption Data: An Elman Neural Network Approach
BT  - Proceedings of the 2024 5th International Conference on Big Data and Informatization Education (ICBDIE 2024)
PB  - Atlantis Press
SP  - 143
EP  - 154
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-417-4_13
DO  - 10.2991/978-94-6463-417-4_13
ID  - Li2024
ER  -