Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

October 30, 2023


Pages


DOI

Article

Analysis of factors influencing police investigation work based on principal component analysis

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Authors

Hao Huang Affiliation:
Guangxi Police College, Nanning, Guangxi, 530028, China.


Abstract

In this paper, the generation and carrier models of criminal psychological traces are synthesized and applied to detect criminal cases by constructing a criminal psychological trace model. Secondly, the psychological state of the interrogated person is identified using the first and second layers of the principal component analysis network, and the psychological characteristics of the interrogated person are extracted based on the grey time series improved principal component analysis (GPCA) method. Finally, the psychological state of the interrogated person was analyzed by the psychological test of the criminal psychological trace model. The results showed that the AUC of the CIT psychological test effect on criminal experience was 0.638, while the CIT psychological test effect using the criminal psychological trace model was 0.875. This indicates that the research method in this paper can better understand the criminal psychological traces in the police investigation and their effects on the interrogated person and improve the effectiveness and accuracy of the police investigation.


Keywords

Criminal psychology, Trace model, Principal component analysis, Gray time series, Police investigation, 97P28


Citation

Huang, H. (2023). Analysis of factors influencing police investigation work based on principal component analysis. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00859

Published by: Engineering Journals

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