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Automatic classification and identification algorithms for single-environment risk and their application in social changes

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  • Pang, Sulin
  • Xia, Lianhu

Abstract

This article focuses on the risk assessment about social environmental safety-. Based on multi-rule, multi-standard, multi-level, multi-factor, and multi-dimension classification principles, this paper proposes a layer-by-layer classification and automatic identification algorithm for single-environment risks. The layer-by-layer classification, k-classification, single-environment risk, and risk information are defined. This paper first proposes an algorithm for the layer-by-layer classification of risk, and -an automatic identification algorithm of layer-by-layer classificationfor single-environment risk. By designing a rule for thelayer-by-layer classification of risk, this paper innovatively studies the automatic identification, evaluation, measurement, and classification of risk in a single environment. The algorithms are applied to a real case where a woman in Dalian, China was suddenly beaten by a stranger in the middle of the night on 22 June 2019. Through four iterations of gradual classification and automatic identification, the environment is finally labeled as "top risk," and a corresponding numerical risk value is calculated. This research is practical and can be used to provide guidance to populations on how to identify and avoid certain risks.

Suggested Citation

  • Pang, Sulin & Xia, Lianhu, 2021. "Automatic classification and identification algorithms for single-environment risk and their application in social changes," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    • Handle: RePEc:eee:tefoso:v:166:y:2021:i:c:s0040162521000743
    DOI: 10.1016/j.techfore.2021.120642
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