Research on population trafficking prediction based on K-means and BP neural network

摘要：

　　This paper mainly analyzes the issue of human trafficking. First, identify high-risk groups and prevent them in time. Using the data collected from countries around the world, the TOPSIS method was used to evaluate the risk of trafficking in countries around the world. The evaluation results were clustered by K-MEANS method and represented by different colors on the map. Second, locate the victim. Taking the United States as an example, we have further refined the location of the victims. By looking at the number of human trafficking cases in each state in 2012-2017, BP neural network was used to predict the number of human trafficking cases in each state in the next four years.

关键词： TOPSIS method K-MEANS neural network graph theory human trafficking

作者: Zhihong Liu Zhongxian Zhu Suxin Liu Xiaoyu Han

作者单位: Harbin Institute of Technology, Harbin, China Harbin University of Science and Technology, Weihai, China

会议类型: 国际会议

会议名称: 2019 6th International Conference on Machinery, Mechanics, Materials and Computer Engineering (MMMCE 2019)(2019 第六届机械、材料和计算机工程国际会议)

会议地点: 呼和浩特

会议语种:英文

页码: 618-625

在线出版日期: 2019-07-27（万方平台首次上网日期，不代表论文的发表时间）