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Identification Of Graduation Project Score Associated Factors Of College Electrical Engineering Based On Data Mining

Posted on:2023-10-10Degree:MasterType:Thesis
Country:ChinaCandidate:Z X YuanFull Text:PDF
GTID:2532306938991559Subject:Statistics
Abstract/Summary:PDF Full Text Request
As an important category of College Engineering Majors,the quality of graduation design has generally shown a downward trend.It is very necessary to study the important factors affecting the results of graduation design.This paper takes 1379 electrical engineering graduates from a B University in Guangdong Province as the research object,and introduces data mining technology into the management practice of electrical engineering.This paper uses software to carry out data preprocessing,such as Excel and SPSS,establishes two models of K-means clustering and fuzzy C-means clustering based on Python language and performs operations respectively,selects variables through lasso regression and establishes multiple linear regression models,Excavate the hidden valuable information and explore the important factors that affect the graduation design results.This paper conducts variance analysis on the average credits and main professional courses based on the grades of graduation design,and finds that there is no significant difference in the average credits and main professional courses of intelligent science and technology majors,there are significant differences between the main professional courses of information engineering,electrical engineering and automation.In this paper,11 grade points such as average credits and circuit analysis foundation are used as feature labels,and graduation design scores are used as output labels.It is found that the number of K-means and FCM clusters is two and the K-means clustering model has better performance,which can more accurately analyze the characteristics of students and professional characteristics.In this paper,the multiple linear regression model is used to predict the grades of the graduation project.The model operation results show that most of the actual values are consistent with the predicted values.At the same time,it is found that the average credits,professional comprehensive practice,and professional comprehensive design are important influencing factors.Pay attention to the teaching quality of professional courses,expand the practice platform,and establish and improve the quality monitoring system for graduation design.
Keywords/Search Tags:Electrical Engineering, Graduation Project, Data Mining, Associated Factors
PDF Full Text Request
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