校园一卡通消费行为的研究与分析

Research and Analysis of Campus Card Consumption Behavior

摘要: 项目通过R语言对校园卡消费信息记录的数据分析，提取统计量得到个人消费特征；依据消费特征和HCO算法建立预测校园内各消费点实时消费人数及工作人员分配模型。通过ARIMA模型预测消费特征，建立校园卡防盗刷模型和“余额–转账”模型，并进一步通过支持向量机和Apirori算法建立贫困生助学金、贷款项目审核分发模型。充分利用校园卡消费大数据，通过数学技术系统全面分析，构建各种为经济、安全服务的数学模型，提高了学生的生活质量并且产生一定的经济效益。

Abstract: The project uses R language to analyze the data of consumption information records of campus cards and extracts statistics to obtain individual consumption characteristics. According to con-sumption characteristics and HCO algorithm, it establishes a real-time consumption number pre-diction model and staff allocation model for each consumption point in campus. The ARIMA model is used to predict consumption characteristics, and the anti-theft brush model and the bal-ance-transfer model of campus cards are established. Furthermore, the support vector machine (SVM) and the Apirori algorithm are used to establish the auditing and distributing model of grants and loans for poor students. The paper makes full use of the big data of campus card consumption, through the comprehensive analysis of mathematical technology system, to build various mathematical models for economic and security services, improve students’ quality of life and produce certain economic benefits.