A study on the psychological relief path of gender stress in women's workplace based on hierarchical analysis

In this paper, we use variable prediction to assess mental health using a spurious nearest neighbor point algorithm to reconstruct mental trajectories, extract group feature vectors and map them into a high-dimensional spatial structure. The standard deviation of Gaussian function centroids is deriv...

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Bibliographic Details
Main Author: Zhang Bo
Format: Article
Language:English
Published: Sciendo 2024-01-01
Series:Applied Mathematics and Nonlinear Sciences
Subjects:
Online Access:https://doi.org/10.2478/amns.2023.2.00562
Description
Summary:In this paper, we use variable prediction to assess mental health using a spurious nearest neighbor point algorithm to reconstruct mental trajectories, extract group feature vectors and map them into a high-dimensional spatial structure. The standard deviation of Gaussian function centroids is derived by combining the radial basis network input implicit layer node parameters. The hierarchical analysis method was used to split the psychological data, and the Lagrange multiplier method was used to reconstruct the psychological space, and it was found that the overall work stress index of women was 78.97 points, and there was no significant difference in the factors of the symptom self-rating scale. It is suggested that enterprises should offer psychological counseling courses, equip professional psychological counselors, scientifically guide employees’ psychological states, and create a gender-equal corporate culture atmosphere.
ISSN:2444-8656