Consumption behavior evaluation of college students based on PSO-DTSVM

2019 2nd International Conference on Advanced Materials, Intelligent Manufacturing and Automation

Chen, Hui^1 ; Wang, Xinze^1 ; Zhou, Yan^1 ; Zhao, Shasha^1^2 ; Zhang, Dengyin^1^2

School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu

210003, China^1

Jiangsu Key Laboratory of Broadband Wireless Communication and Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu

210003, China^2

关键词: Behavior evaluations;    Classification accuracy;    Classification standard;    College students;    Consumption index;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/569/5/052104/pdf
DOI  :  10.1088/1757-899X/569/5/052104

来源: IOP

【 摘 要 】

Blind and reckless consumption of the college students has become a common phenomenon. To give a correctly guiding, a decision tree support vector machine (DTSVM) based on particle swarm optimization (PSO) used to evaluate college students consumption behaviour is proposed in this paper. Firstly, the classification standard of college students consumption was derived with the investigation and data analysis. Then, the consumption ability and habits for different students are divided into four categories. Lastly, the targeted consumption index is fed back for the corresponding students. Experiment results show that a classification accuracy of 99.79% can be achieved, which will provide better guidance for the college students' consumption behaviour.