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Research on Suicide Risk Spectrum of Prisoners Based on Fourier Transform

In: City, Society, and Digital Transformation

Author

Listed:
  • Sainan Gao

    (Nanjing University of Aeronautics and Astronautics)

  • Yang Shen

    (Nanjing University of Aeronautics and Astronautics)

Abstract

Prisoner suicide risk prevention and control cannot be ignored, yet there is a lack of relevant quantitative studies to support risk management. We quantify the risk of prisoner suicide based on the Fourier transform, establish a relevant data model, and examine the impact of different frequencies of influencing factors on the overall risk of prisoner suicide through simulation. At the same time, we innovatively use Fourier transform to obtain the frequency spectrum of prisoner suicide risk data, and conduct frequency domain analysis. The simulation results show that negative events are the most influential factor on the overall prisoner suicide risk, and the frequency domain analysis provides the cyclical characteristics of suicide risk for different types of prisoners. We emphasize the importance of fairness in prison enforcement to reduce the occurrence of negative events and the need for periodic suicide screening and prevention based on the behavioral characteristics of prisoners.

Suggested Citation

  • Sainan Gao & Yang Shen, 2022. "Research on Suicide Risk Spectrum of Prisoners Based on Fourier Transform," Lecture Notes in Operations Research, in: Robin Qiu & Wai Kin Victor Chan & Weiwei Chen & Youakim Badr & Canrong Zhang (ed.), City, Society, and Digital Transformation, chapter 0, pages 191-202, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-15644-1_15
    DOI: 10.1007/978-3-031-15644-1_15
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