期刊文献+

Using Radial-basis Function Network for CLV

Using Radial-basis Function Network for CLV
下载PDF
导出
摘要 Analysis and comparing with three existing and popularly used forcasting customer lifetime value (CLV) methods, which are the Dwyer method, customer event\|method and fitting method, and using performances of the existent artificial neural network, we apply the Radial basis Function(RBF) network to forecast the CLV, the RBF network can approach the objective function partially. To every input/output pairs, it only needs adjust the weight a little and learn quickly which is very important to the forecast precision. Simulation and experimental results on the customers’ data of a company in Shaanxi Province reveal the effectiveness and feasibility of the RBF network.\; Analysis and comparing with three existing and popularly used forcasting customer lifetime value (CLV) methods, which are the Dwyer method, customer event\|method and fitting method, and using performances of the existent artificial neural network, we apply the Radial basis Function(RBF) network to forecast the CLV, the RBF network can approach the objective function partially. To every input/output pairs, it only needs adjust the weight a little and learn quickly which is very important to the forecast precision. Simulation and experimental results on the customers' data of a company in Shaanxi Province reveal the effectiveness and feasibility of the RBF network.\;
出处 《成组技术与生产现代化》 2002年第3期53-56,共4页 Group Technology & Production Modernization
基金 ThisresearchsupportedbyNSFC (70 12 10 0 1)andtheEducationDep artmentofShaanxiProvince (0 2JK0 0 9) .
关键词 BP网络 BRF网络 CLV 客户价值 BRF network customer lifetime value customer value
  • 相关文献

参考文献11

  • 1Lyette Ryals, SimonKnox.Cross-Functional Issues in the Implementation of Relationship Marketing ThroughCustomer Relationship Management[J]. European Management Journal, 2001,19(5):534-542.
  • 2Emma Chablo. The Importance of Marketing Data Intelligence in Delivering SuccessfulCRM[M]. FOCUS :White paper of smart,1999.
  • 3Dwyer,Robert F. Customer Lifetime Valuation to Support Marketing DecisionMaking[J]. Journal of Direct Marketing,1989, 8 (2): 73-81.
  • 4Dwyer, Robert F, Schurr,et al . Developing Buyer- Seller Relations[J]. Journal ofMarketing,1997, 51(8): 11-28.
  • 5Berger, Paul D, Nada I, et al . Customer Lifetime Value: Marketing Models andApplications[J]. Journal of Interactive Marketing,1998, 12 (Winter), 17-30
  • 6Pitt, Leyland F, Ewing,et al .Turning Competitive Advantage into CustomerEquity[J]. Business Horizons, 2000,43 (9-10): 11-18.
  • 7Qube Consulting Limited. Predicting and Using Customer Lifetime Value to ImproveProfitability[EB/OL]. http://www.crm-forum.com,2000.
  • 8Chen M L. Research on Customer Retention and Lifetime Cycle, Doctoral Dissertation[D].Xi'an Jiaotong University, 2001,35-52. (in Chinese)
  • 9Afsar Saranli, Buyurman Baykal. Complexity reduction in redial basis function (RBF)networks by using radial B-spline functions[J]. Neurocomputing, 1998,18: 183-194.
  • 10Tan K K, Tang K Z. Taguchi-tuned radial basis function with application to highprecision motion control[J]. Artificial Intelligence in Engineering, 2001, 15: 25-36.

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部