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Lanlan Yin

Biographic Data

ID8239782
NAMELanlan Yin
GIVEN NAMESLanlan
FAMILY NAMEYin
SIGNATUREYIN L
AFFILIATIONSHechi University
VERIFIEDNo
TOTAL WORKS1
TOTAL CITATIONS0
WORKS AS AUTHOR1
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2026
LATEST PUBLICATION YEAR2026
H-INDEX0
  • A study on the factors influencing university students’ subjective well-being based on machine learning methods

    Open Access•Yunkun Zhang, Muhammad Syawal Amran et al.•ARTICLE•BMC Psychology•2026

    Subjective well-being is a key area of research in psychology. Based on survey data from 384 university students, this study employed automated machine learning methods to construct a predictive model of subjective well-being, in which the Support Vector Machine (SVM) model performed best, achieving an overall prediction accuracy of 81.81%. The results indicate that the overall subjective well-being of the current university student population is…

No prominent works on this page.

  • A study on the factors influencing university students’ subjective well-being based on machine learning methods

    Open Access•Yunkun Zhang, Muhammad Syawal Amran et al.•ARTICLE•BMC Psychology•2026

    Subjective well-being is a key area of research in psychology. Based on survey data from 384 university students, this study employed automated machine learning methods to construct a predictive model of subjective well-being, in which the Support Vector Machine (SVM) model performed best, achieving an overall prediction accuracy of 81.81%. The results indicate that the overall subjective well-being of the current university student population is…

Animal learning (1 work) · Educational Technology and Pedagogy (1 work) · Experimental psychology (1 work) · Mental Health via Writing (1 work) · Psychological research (1 work) · Psychological Well-being and Life Satisfaction (1 work) · Research methodology (1 work)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae