A Fuzzy Neural Network Model with Application to Telecommunications Business
There are many factors involved in a revenue-forecasting problem of telecommunications business (TB), which are not independent and conflicted with each other. The traditional methods of forecasting TB revenues are based on regression analysis, but the precisions of the results are usually not satisfied in practice. In this study, statistical analysis is first used to evaluate factors and then the main factors are selected as inputs to construct a neural network model combined with fuzzy rules. Furthermore, the fuzzy neural network (FNN) model is applied to predict the revenue of a specific telecommunications business. The results indicate that the developed FNN model satisfies practical requirements and is possible to expand to other business applications, such as customers evaluation and financial risk pre-warning. To make this clearer, an illustrative example is given for demonstration.
Yongping Li Rongjun Li
School of Business Administration, South China University of Technology Guangzhou city, Guangdong Province, 510640, P.R.China
国际会议
2006 Asia-Pacific Services Computing Conference(IEEE亚太地区服务计算会议)
广州
英文
112-117
2006-12-12（万方平台首次上网日期，不代表论文的发表时间）