›› 2016, Vol. 28 ›› Issue (11): 245-251.

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A Risk Early Warning Method for High-risk Groups of Social Security Based on Support Vector Machine

Zhang Qiang1,2, He Leping1   

  1. 1. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190;
    2. The People's Government of Ji'an, Ji'an 343000
  • Received:2016-05-09 Online:2016-11-28 Published:2016-11-23

Abstract:

With the rapid development of economy and mobility of population, public security has been facing new challenges. To timely deal with the complicated and changing risk of public security, a key step is to improve the ability of risk early warning of potentially high-risk groups. In this paper we use support vector machine (SVM) algorithm to build a risk early warning model, which shows a cer-tain guiding significance to an effective early-warning on high-risk groups.

Key words: high-risk groups, public security, risk early warning, support vector machine