{"title":"Prediction model based on Gompertz function","authors":"Zheng Yan","doi":"10.1109/ICBNMT.2009.5347813","DOIUrl":null,"url":null,"abstract":"A novel prediction model based on Gompertz function and Customer Life Cycle (CLC) is presented in this paper. Firstly, the calling behavior between the inner-net (China Unicom) mobile customers and the outer-net (China Mobile) mobile customers are extracted and analyzed, then fitted a CLC curve by Gompertz function. Furthermore, the different period of CLC is identified according to the fitting curve. Finally the number of outer-net mobile customers is predicted accurately and dynamically. The experiments of real data illustrate the availability and accuracy of the proposed prediction model.","PeriodicalId":267128,"journal":{"name":"2009 2nd IEEE International Conference on Broadband Network & Multimedia Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd IEEE International Conference on Broadband Network & Multimedia Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBNMT.2009.5347813","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A novel prediction model based on Gompertz function and Customer Life Cycle (CLC) is presented in this paper. Firstly, the calling behavior between the inner-net (China Unicom) mobile customers and the outer-net (China Mobile) mobile customers are extracted and analyzed, then fitted a CLC curve by Gompertz function. Furthermore, the different period of CLC is identified according to the fitting curve. Finally the number of outer-net mobile customers is predicted accurately and dynamically. The experiments of real data illustrate the availability and accuracy of the proposed prediction model.