FORECAST OF THE REGIONAL EC DEVELOPMENT THROUGH AN IMPROVED ANN MODEL
The paper endeavors to make a forecast study of the regional E-Commerce development level with an improved Artificial Neural Networks (ANN) forecast model, it mainly consists of the following: (1) Setting up an improved ANN forecast model, that is, the Back Propagation Networking Learning Algorithm (BP Networking Algorithm) with an interference function. (2) Setting up a relatively complete and workable evaluation index system for passing judgment on the regional E-business development level; (3) On the basis of the models and evaluation index system established, an forecast study of the E-Commerce development level in a certain city in China was carried out. The result of the case study has indicated that the model has an ideal extension, the number of its hidden-layer neurons can easily be decided, and it is relatively easy to have a long-term forecast of the E-Commerce development without much initial data. With this model in hand, it is possible to cope with the problems of sparse, dispersed and hard-to-forecast statistical information in the development of the electronic commerce.
Interference function BP model EC development Forecast
Guo Jianquan Fan Kun Tang Bingyong Bright Shi Yang Jianzheng
Donghua University;University of Shanghai for Science and Technology Shanghai Maritime University Donghua University University of Shanghai for Science and Technology
国际会议
5th International Conference on e-Engineering & Digital Enterprise Technology(第5届e工程及数字企业国际学术会议)
贵阳
英文
1-5
2006-08-16（万方平台首次上网日期，不代表论文的发表时间）