Analysis and Research of Psychological Education Based on Data Mining Technology

Sang, Haiyun

doi:10.1155/2021/8979507

Cited by 14 publications

(11 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As shown in Figure 9 and Figure 10, the index RMSE of the psychological fitting prediction method for college students proposed in this paper is 37.21, which is 1.91 and 1.19 lower than that in reference (Wang, 2021) and reference (Sang, 2021). For the indicator MAE, the index value of the proposed method is 0.33, while that of reference (Wang, 2021) and reference (Sang, 2021) is both 0.399.…”

Section: Experimental Optimization Analysismentioning

confidence: 74%

“…Aiming to verify the performance superiority of the early warning method of student psychological crisis proposed in this paper, this paper uses reference (Wang, 2021) and reference (Sang, 2021) as Figure 9 shows the RMSE indicators under different methods. Furthermore, this paper also conducts a quantitative analysis on MAE indicator variables.…”

Section: Experimental Optimization Analysismentioning

confidence: 99%

“…Reference (Wang, 2021) established a statistical analysis model for the psychological rescue function of music education through the method of fuzzy feature extraction. Reference (Sang, 2021) collects students' psychological state data and analyzes the psychological crisis state based on support vector machine. Reference (Pang, 2021) used the big data analysis technology and the decision tree algorithm to establish a psychological assessment model to achieve accurate psychological assessment and early warning.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Early Warning Model of College Students' Psychological Crises Based on Big Data Mining and SEM

Liu

2023

International Journal of Information Technologies and Systems Approach

View full text Add to dashboard Cite

In recent years, the psychological problems of college students could not be ignored, as they have seriously affected the growth of students and the normal teaching order of colleges and universities. However, there exists a strong noise in college students' psychological sample data set and a strong correlation between its data. Aiming to solve this problem, this paper proposes a psychological crisis warning method for college students based on big data mining and structural equation model (SEM). This method is oriented to massive user data in social networks. Particle swarm optimization is introduced to improve the random forest algorithm, and the original data is labeled to alleviate the impact of data noise on the recognition accuracy. The simulation example comes from an efficient actual data set in the southern China. The experimental results show that the proposed method can achieve an efficient analysis of actual complex data, and can provide reliable psychological auxiliary diagnosis for practitioners.

show abstract

Section: Experimental Optimization Analysismentioning

confidence: 74%

Section: Experimental Optimization Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Early Warning Model of College Students' Psychological Crises Based on Big Data Mining and SEM

Liu

2023

International Journal of Information Technologies and Systems Approach

View full text Add to dashboard Cite

show abstract

“…Sang H uses the theoretical principles and policies of technological innovation and ecological civilization construction to conduct research on how to promote green development through technological innovation and progress and practice the concept of environmental protection. This has played a certain role in promoting the concept of sustainable development in my country and practicing the value theory of ecological civilization has a positive effect [ 23 ]. Geng et al's green economy emphasizes the word “green.” His main representative works are new energy, and the following have developed low-carbon related industries, low-carbon technologies, green products beneficial to mankind, new finance characterized by green investment, and green grid system [ 24 ].…”

Section: Related Workmentioning

confidence: 99%

Application of Data Mining Technology in Enterprise Green Innovation Model Construction and Path Analysis

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Since sustainable development has become the dominant mode of human development at the present stage, green technology has received more and more attention under this background. The development of green technology has become an important means to achieve sustainable development. Green technological innovation is a kind of technological innovation. However, because the goal of green technological innovation is different from that of traditional technological innovation, the dynamic mechanism of green technological innovation lies in the similarities and differences of traditional technological innovation. This paper focuses on data mining technology to design and optimize the enterprise green technology creation model. At present, clustering algorithm and association rule algorithm are important research contents in big data mining technology. Among them, the clustering algorithm refers to the process of grouping similar data objects in a large amount of data information, so that the approximate data information can be aggregated and clustered, which is convenient for data mining calculation. In the algorithm, the shortcomings of the original clustering algorithm, such as insufficient data processing and incomplete analysis, are improved, and the data processing is improved by 51.7%, which has a good processing effect on subsequent data preprocessing and dynamic incremental clustering. In the follow-up experiment, the role of green technology in corporate finance is reflected.

show abstract

“…Only by examining the current state of mental health of college students in China today in a timely and legal manner can we solve their mental health problems. According to the goals and objectives and the development of new technologies in our country ( Sang, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Application of data mining technology in college mental health education

Sun

2022

Front. Psychol.

View full text Add to dashboard Cite

In order to improve education and teaching methods and meet the “heart” needs of college students in the era of big data, this paper analyzes the application of data mining technology in college mental health education, and introduces database technology and decision tree algorithm to support college mental health work. This process verifies the feasibility of this kind of system with the help of an example. Using the test standards outlined in this document, 1.5 previous test tasks were completed within the timeframe. During the system test, the error rate was 14% and the number of tests was 7%.However, the error rate in the development stage is 11%, which is lower than 19% of the old version. The error rate in the acceptance stage is 14%, which is lower than 5% of the old version. That is to say, most of the errors were found in time in the system analysis and design stage. 14% of the problems found in the development stage are basically small problems in the interface display, which do not need major changes. However, the old version also includes design defects found in the development stage, and only large-scale rewriting of the involved modules. In the research process, the work of mental health in Colleges and universities has been promoted. At this time, the law of psychological changes of college students has been summarized. Therefore, the support of data mining technology can better meet the needs of mental health education in Colleges and universities.

show abstract

Analysis and Research of Psychological Education Based on Data Mining Technology

Cited by 14 publications

References 23 publications

Early Warning Model of College Students' Psychological Crises Based on Big Data Mining and SEM

Early Warning Model of College Students' Psychological Crises Based on Big Data Mining and SEM

Application of Data Mining Technology in Enterprise Green Innovation Model Construction and Path Analysis

Application of data mining technology in college mental health education

Contact Info

Product

Resources

About