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Z. H. Han and X. X. Zhu, “Selection of Training Sample Length in Support Vector Regression Based on Information Entropy,” Proceedings of the CSEE, Vol. 30, No. 20, 2010, pp. 112-116.

has been cited by the following article:

• TITLE: Research on the Prediction Model for the Security Situation of Metro Station Based on PSO/SVM

  AUTHORS: Yong Qin, Zhenyu Zhang, Bo Chen, Zongyi Xing, Jing Liu, Jun Li

  KEYWORDS: Situation Awareness; Situation Prediction; Index System; PSO; SVM

  JOURNAL NAME: Journal of Intelligent Learning Systems and Applications, Vol.5 No.4, November 26, 2013

  ABSTRACT: Security situation awareness is a new technology about security. This paper brings it to the assessment of security situation of metro station which serves as a new way to secure the security of passengers as well as the operation of the metro station. This paper sets up an index system for assessing the security situation awareness and makes a prediction model for the security situation of metro station based on PSO/SVM after doing lots of researches and analyses. Furthermore, through case studies, we find that the model has high accuracy and ability to accurately predict the security situation of metro station in the future and a certain practical value.