“拍照赚钱”任务定价方案的评价与优化  

Evaluation and optimization of "photo-earning" task pricing scheme

作　　者：张敏[1] 吴启红 ZHANG Min;WU Qi-liong(School of Statistics And Appl Matli,Anhui University of Finance and Economics,Anhui Bengbu 233030,China)

机构地区：[1]安徽财经大学统计与应用数学学院,安徽蚌埠233030

出　　处：《贵阳学院学报（自然科学版）》2018年第1期78-81,共4页Journal of Guiyang University：Natural Sciences

基　　金：安徽财经大学大学生创客实验室(项目编号:acdxsck201707)

摘　　要：针对"互联网+"时代下"拍照赚钱"的任务定价方案。首先,采用集合的思想,根据附件中样本点会员位置信息,根据映射关系式计算得出任务完成便利度指标数据;其次,基于二分类Logistic回归模型的思想,引入任务完成便利度指标以及其后期计算方式地不断深化,得到相对全面的Logistic回归模型。最后,运用神经网络模型进行训练和优化,综合运用了MATLAB、STATA软件进行编程求解,最终得到在个体打包发放的情况下,样本容量越大,保证相同的任务成功率的情况下,所需定价成本越小的结论。the task pricing scheme for’’taking photos and making money’’under the’’Internet d"era.Firstly,idea of collection,according to the information of the sample points in the attachment,the data of of thie tasl^s are obtained according to the mapping relational calculation.Secondly,based on the thought Logistic regression models,the introduction of thie tasl^completion convenience index and the continuous of its later calculation methods are given a relatively comprehensive Logistic regression model.Finally,using network model was trained and optimized,integrated use of the MATLAB,STATAsoftware programming the case of individual packaging issue,sample size,the greater the guarantee under the condition of the same mission the conclusion of the required price cost is smaller.

关 键 词：拍照赚钱 二分类Logistic回归模型 神经网络模型 MATLAB 

分 类 号：F299.23[经济管理—国民经济]