Time prediction of serial criminals based on commensurability. Issue 4 (3rd July 2016)
- Record Type:
- Journal Article
- Title:
- Time prediction of serial criminals based on commensurability. Issue 4 (3rd July 2016)
- Main Title:
- Time prediction of serial criminals based on commensurability
- Authors:
- Feng, Lichao
Hao, Shengnan
Zhao, Yongsheng
Zhang, Chunyan - Abstract:
- Abstract: Twisted souls and antisocial spirits have resulted in serial criminals. In order to prevent such crimes which cause great harm to public security, the paper has established a kind of quickly and effective scheme to help the policemen to arrest the criminals based on commensurability theory. Taking the criminal of "Yorkshire Ripper" as an example, we compile the procedures of commensurability of ternary, quaternion and quintuple of his criminal time. And the model is very accurate because the predicted value based on the commensurability theory equals to the actual value. When facing others serial criminals, commensurability theory can also be applied to predict the possible coming criminal time using the time of past criminals. Obviously, the scheme we established is also helpful to build a harmonious society.
- Is Part Of:
- Journal of interdisciplinary mathematics. Volume 19:Issue 4(2016)
- Journal:
- Journal of interdisciplinary mathematics
- Issue:
- Volume 19:Issue 4(2016)
- Issue Display:
- Volume 19, Issue 4 (2016)
- Year:
- 2016
- Volume:
- 19
- Issue:
- 4
- Issue Sort Value:
- 2016-0019-0004-0000
- Page Start:
- 635
- Page End:
- 643
- Publication Date:
- 2016-07-03
- Subjects:
- Commensurability -- Criminal -- Time prediction
Mathematics Subject Classification: 62L99
Mathematics -- Periodicals
Mathematics
Periodicals
510.5 - Journal URLs:
- http://www.iospress.nl/html/09720502.php ↗
http://www.tandfonline.com/loi/tjim20 ↗ - DOI:
- 10.1080/09720502.2016.1179484 ↗
- Languages:
- English
- ISSNs:
- 0972-0502
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 36.xml