Analysis of College Student Registration Management and Change Prediction Based on Mutated Fuzzy Neural Network Algorithm

Nowadays, a large number of students' academic registrations change every year in universities, but most of these cases are recorded and mathematically and statistically analysed through forms or systems, which are cumbersome and difficult to find some potential information in them. Therefore,...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yao Wang, Lie Jiao, Chunzhi Liu
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/a0c21711dca64c2b993517577422009b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:a0c21711dca64c2b993517577422009b
record_format	dspace
spelling	oai:doaj.org-article:a0c21711dca64c2b993517577422009b2021-11-29T00:56:44ZAnalysis of College Student Registration Management and Change Prediction Based on Mutated Fuzzy Neural Network Algorithm1687-527310.1155/2021/7097425https://doaj.org/article/a0c21711dca64c2b993517577422009b2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/7097425https://doaj.org/toc/1687-5273Nowadays, a large number of students' academic registrations change every year in universities, but most of these cases are recorded and mathematically and statistically analysed through forms or systems, which are cumbersome and difficult to find some potential information in them. Therefore, timely and effective prediction of student registration changes and early warning of student registration changes by technical means is an important part of university registration management. At present, relevant research is mostly based on mathematical statistical analysis methods such as students' current credit evaluation or course score averages and seldom uses data mining and other technical methods for in-depth research. In this paper, we propose a mutated fuzzy neural network (MFNN) based prediction model for student registration changes in colleges and universities, which can provide supplementary reference decisions for school registration management for school teaching managers. In this paper, we first construct the corresponding prediction model of academic registration variation, define the relevant parameters, and model the optimization problem and propose the objective optimization function. Second, the proposed model is optimized by adding principal component analysis (PCA) to the original model to improve the efficiency of model training and the correct prediction rate. It is verified that the proposed model can effectively predict individual students' academic registration changes with a prediction accuracy of nearly 92.91%.Yao WangLie JiaoChunzhi LiuHindawi LimitedarticleComputer applications to medicine. Medical informaticsR858-859.7Neurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENComputational Intelligence and Neuroscience, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Yao Wang Lie Jiao Chunzhi Liu Analysis of College Student Registration Management and Change Prediction Based on Mutated Fuzzy Neural Network Algorithm
description	Nowadays, a large number of students' academic registrations change every year in universities, but most of these cases are recorded and mathematically and statistically analysed through forms or systems, which are cumbersome and difficult to find some potential information in them. Therefore, timely and effective prediction of student registration changes and early warning of student registration changes by technical means is an important part of university registration management. At present, relevant research is mostly based on mathematical statistical analysis methods such as students' current credit evaluation or course score averages and seldom uses data mining and other technical methods for in-depth research. In this paper, we propose a mutated fuzzy neural network (MFNN) based prediction model for student registration changes in colleges and universities, which can provide supplementary reference decisions for school registration management for school teaching managers. In this paper, we first construct the corresponding prediction model of academic registration variation, define the relevant parameters, and model the optimization problem and propose the objective optimization function. Second, the proposed model is optimized by adding principal component analysis (PCA) to the original model to improve the efficiency of model training and the correct prediction rate. It is verified that the proposed model can effectively predict individual students' academic registration changes with a prediction accuracy of nearly 92.91%.
format	article
author	Yao Wang Lie Jiao Chunzhi Liu
author_facet	Yao Wang Lie Jiao Chunzhi Liu
author_sort	Yao Wang
title	Analysis of College Student Registration Management and Change Prediction Based on Mutated Fuzzy Neural Network Algorithm
title_short	Analysis of College Student Registration Management and Change Prediction Based on Mutated Fuzzy Neural Network Algorithm
title_full	Analysis of College Student Registration Management and Change Prediction Based on Mutated Fuzzy Neural Network Algorithm
title_fullStr	Analysis of College Student Registration Management and Change Prediction Based on Mutated Fuzzy Neural Network Algorithm
title_full_unstemmed	Analysis of College Student Registration Management and Change Prediction Based on Mutated Fuzzy Neural Network Algorithm
title_sort	analysis of college student registration management and change prediction based on mutated fuzzy neural network algorithm
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/a0c21711dca64c2b993517577422009b
work_keys_str_mv	AT yaowang analysisofcollegestudentregistrationmanagementandchangepredictionbasedonmutatedfuzzyneuralnetworkalgorithm AT liejiao analysisofcollegestudentregistrationmanagementandchangepredictionbasedonmutatedfuzzyneuralnetworkalgorithm AT chunzhiliu analysisofcollegestudentregistrationmanagementandchangepredictionbasedonmutatedfuzzyneuralnetworkalgorithm
_version_	1718407664233349120

Analysis of College Student Registration Management and Change Prediction Based on Mutated Fuzzy Neural Network Algorithm

Ejemplares similares