Abstract
In order to recognize the criminal suspects in the crowd relevant to the case by computer and improve the efficiency of solving the case, this paper presents a new method of suspected culprit recognition based on Probit model. Separation algorithm, correlation algorithm based on cluster and the parameters named significance level in Probit model are adopted to find the important attributes of the culprit, and then, by training the data just including the important attributes, the crime risk evaluation model could be achieved. The experimental results show that average accuracy of model-recognizing-culprit is 90.5% and the average recall is 92.7%.
| Original language | English |
|---|---|
| Pages (from-to) | 1337-1341 |
| Number of pages | 5 |
| Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
| Volume | 31 |
| Issue number | 11 |
| Publication status | Published - Nov 2011 |
Keywords
- Cluster
- Crime risk judge
- Probit model
- Suspect recognition
