Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network

Jia Wang; Zijie Zhang; Haiji Luo; Yinghao Liu; Wei Chen; Gang Wei

doi:doi:10.11648/j.ajap.20190806.12

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Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network

Jia Wang, Zijie Zhang, Haiji Luo, Yinghao Liu, Wei Chen, Gang Wei

Published in American Journal of Applied Psychology (Volume 8, Issue 6)

Received: 26 October 2019 Accepted: 18 November 2019 Published: 26 November 2019

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Abstract

With the continuous advancement of information construction in colleges and universities, a large number of student data have been accumulated and precipitated in the campus center database of colleges and universities. On the basis of social constructivist psychology, Maslow and Mittelmann's mental health standards and related research results of psychological crisis early warning, three first-level indicators and 15 second-level indicators of college student’s psychological crisis were established. The campus data of 1504 college students were collected on one data center of a college, and the weight of each indicator was determined on the basis of correlation analysis of each indicator and psychological status indicators through SPSS21.0 and the expert opinion. The early warning model of college students’ psychological crisis was basically constructed. With experimental simulation of 250 sets of real data, the early warning model based on the genetic BP Neural network for its initial weight and threshold with MATLAB was improved. The results indicated that the indicator system of college student’s psychological crisis in this paper was effective and feasible, and the early warning model based on genetic BP neural network had high accuracy and certain application value.

Published in	American Journal of Applied Psychology (Volume 8, Issue 6)
DOI	10.11648/j.ajap.20190806.12
Page(s)	112-120
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

College Student, Psychological Crisis Early Warning Model, Genetic BP Neural Network

References

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APA Style

Jia Wang, Zijie Zhang, Haiji Luo, Yinghao Liu, Wei Chen, et al. (2019). Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network. American Journal of Applied Psychology, 8(6), 112-120. https://doi.org/10.11648/j.ajap.20190806.12

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ACS Style

Jia Wang; Zijie Zhang; Haiji Luo; Yinghao Liu; Wei Chen, et al. Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network. Am. J. Appl. Psychol. 2019, 8(6), 112-120. doi: 10.11648/j.ajap.20190806.12

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AMA Style

Jia Wang, Zijie Zhang, Haiji Luo, Yinghao Liu, Wei Chen, et al. Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network. Am J Appl Psychol. 2019;8(6):112-120. doi: 10.11648/j.ajap.20190806.12

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@article{10.11648/j.ajap.20190806.12,
  author = {Jia Wang and Zijie Zhang and Haiji Luo and Yinghao Liu and Wei Chen and Gang Wei},
  title = {Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network},
  journal = {American Journal of Applied Psychology},
  volume = {8},
  number = {6},
  pages = {112-120},
  doi = {10.11648/j.ajap.20190806.12},
  url = {https://doi.org/10.11648/j.ajap.20190806.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajap.20190806.12},
  abstract = {With the continuous advancement of information construction in colleges and universities, a large number of student data have been accumulated and precipitated in the campus center database of colleges and universities. On the basis of social constructivist psychology, Maslow and Mittelmann's mental health standards and related research results of psychological crisis early warning, three first-level indicators and 15 second-level indicators of college student’s psychological crisis were established. The campus data of 1504 college students were collected on one data center of a college, and the weight of each indicator was determined on the basis of correlation analysis of each indicator and psychological status indicators through SPSS21.0 and the expert opinion. The early warning model of college students’ psychological crisis was basically constructed. With experimental simulation of 250 sets of real data, the early warning model based on the genetic BP Neural network for its initial weight and threshold with MATLAB was improved. The results indicated that the indicator system of college student’s psychological crisis in this paper was effective and feasible, and the early warning model based on genetic BP neural network had high accuracy and certain application value.},
 year = {2019}
}

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TY  - JOUR
T1  - Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network
AU  - Jia Wang
AU  - Zijie Zhang
AU  - Haiji Luo
AU  - Yinghao Liu
AU  - Wei Chen
AU  - Gang Wei
Y1  - 2019/11/26
PY  - 2019
N1  - https://doi.org/10.11648/j.ajap.20190806.12
DO  - 10.11648/j.ajap.20190806.12
T2  - American Journal of Applied Psychology
JF  - American Journal of Applied Psychology
JO  - American Journal of Applied Psychology
SP  - 112
EP  - 120
PB  - Science Publishing Group
SN  - 2328-5672
UR  - https://doi.org/10.11648/j.ajap.20190806.12
AB  - With the continuous advancement of information construction in colleges and universities, a large number of student data have been accumulated and precipitated in the campus center database of colleges and universities. On the basis of social constructivist psychology, Maslow and Mittelmann's mental health standards and related research results of psychological crisis early warning, three first-level indicators and 15 second-level indicators of college student’s psychological crisis were established. The campus data of 1504 college students were collected on one data center of a college, and the weight of each indicator was determined on the basis of correlation analysis of each indicator and psychological status indicators through SPSS21.0 and the expert opinion. The early warning model of college students’ psychological crisis was basically constructed. With experimental simulation of 250 sets of real data, the early warning model based on the genetic BP Neural network for its initial weight and threshold with MATLAB was improved. The results indicated that the indicator system of college student’s psychological crisis in this paper was effective and feasible, and the early warning model based on genetic BP neural network had high accuracy and certain application value.
VL  - 8
IS  - 6
ER  -

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Author Information

Jia Wang

College of Medical Informatics, Chongqing Medical University, Chongqing, China
Zijie Zhang

College of Medical Informatics, Chongqing Medical University, Chongqing, China
Haiji Luo

College of Medical Informatics, Chongqing Medical University, Chongqing, China
Yinghao Liu

College of Medical Informatics, Chongqing Medical University, Chongqing, China
Wei Chen

College of Medical Informatics, Chongqing Medical University, Chongqing, China
Gang Wei

College of Electrical Engineering, Chongqing University of Science Technology, Chongqing, China

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Plain Text BibTeX RIS

APA Style

Jia Wang, Zijie Zhang, Haiji Luo, Yinghao Liu, Wei Chen, et al. (2019). Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network. American Journal of Applied Psychology, 8(6), 112-120. https://doi.org/10.11648/j.ajap.20190806.12

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ACS Style

Jia Wang; Zijie Zhang; Haiji Luo; Yinghao Liu; Wei Chen, et al. Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network. Am. J. Appl. Psychol. 2019, 8(6), 112-120. doi: 10.11648/j.ajap.20190806.12

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AMA Style

Jia Wang, Zijie Zhang, Haiji Luo, Yinghao Liu, Wei Chen, et al. Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network. Am J Appl Psychol. 2019;8(6):112-120. doi: 10.11648/j.ajap.20190806.12

Copy | Download

@article{10.11648/j.ajap.20190806.12,
  author = {Jia Wang and Zijie Zhang and Haiji Luo and Yinghao Liu and Wei Chen and Gang Wei},
  title = {Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network},
  journal = {American Journal of Applied Psychology},
  volume = {8},
  number = {6},
  pages = {112-120},
  doi = {10.11648/j.ajap.20190806.12},
  url = {https://doi.org/10.11648/j.ajap.20190806.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajap.20190806.12},
  abstract = {With the continuous advancement of information construction in colleges and universities, a large number of student data have been accumulated and precipitated in the campus center database of colleges and universities. On the basis of social constructivist psychology, Maslow and Mittelmann's mental health standards and related research results of psychological crisis early warning, three first-level indicators and 15 second-level indicators of college student’s psychological crisis were established. The campus data of 1504 college students were collected on one data center of a college, and the weight of each indicator was determined on the basis of correlation analysis of each indicator and psychological status indicators through SPSS21.0 and the expert opinion. The early warning model of college students’ psychological crisis was basically constructed. With experimental simulation of 250 sets of real data, the early warning model based on the genetic BP Neural network for its initial weight and threshold with MATLAB was improved. The results indicated that the indicator system of college student’s psychological crisis in this paper was effective and feasible, and the early warning model based on genetic BP neural network had high accuracy and certain application value.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Research on Early Warning Model of College Students' Psychological Crisis Based on Genetic BP Neural Network
AU  - Jia Wang
AU  - Zijie Zhang
AU  - Haiji Luo
AU  - Yinghao Liu
AU  - Wei Chen
AU  - Gang Wei
Y1  - 2019/11/26
PY  - 2019
N1  - https://doi.org/10.11648/j.ajap.20190806.12
DO  - 10.11648/j.ajap.20190806.12
T2  - American Journal of Applied Psychology
JF  - American Journal of Applied Psychology
JO  - American Journal of Applied Psychology
SP  - 112
EP  - 120
PB  - Science Publishing Group
SN  - 2328-5672
UR  - https://doi.org/10.11648/j.ajap.20190806.12
AB  - With the continuous advancement of information construction in colleges and universities, a large number of student data have been accumulated and precipitated in the campus center database of colleges and universities. On the basis of social constructivist psychology, Maslow and Mittelmann's mental health standards and related research results of psychological crisis early warning, three first-level indicators and 15 second-level indicators of college student’s psychological crisis were established. The campus data of 1504 college students were collected on one data center of a college, and the weight of each indicator was determined on the basis of correlation analysis of each indicator and psychological status indicators through SPSS21.0 and the expert opinion. The early warning model of college students’ psychological crisis was basically constructed. With experimental simulation of 250 sets of real data, the early warning model based on the genetic BP Neural network for its initial weight and threshold with MATLAB was improved. The results indicated that the indicator system of college student’s psychological crisis in this paper was effective and feasible, and the early warning model based on genetic BP neural network had high accuracy and certain application value.
VL  - 8
IS  - 6
ER  -

Copy | Download