Study on Identifying Method of Citys Industry Life Cycle Based on Integration of Rough Sets and Neural Network

摘要：

Against the background of urban economy, an identifying method of citys industry life cycle is put forward based on integration of rough sets and RBF neural network. At first, the continuous attribute values are discretized using fuzzy clustering algorithm based on maximum discernibility value (MDV) search method and information entropy. And then the major attributes are reduced by rough sets. At last, the RBF neural network is trained with training samples and the industry life cycle stages of testing samples are identified. The analysis results taking 669 industries of Dalian city as samples show that the fuzzy clustering algorithm based on MDV and information entropy can improve the discretization performance effectively. Compared with normal fuzzy evaluation method, the predicting precision of integration method is higher, and it is an efficient and practical tool to identify life cycle of citys industry.

关键词： rough sets RBF neural network citys industry life cycle identifying method

作者: Delu Wang Yun Liu

作者单位: School of Management, China University of Mining and Technology, P.R.China

会议类型: 国际会议

会议名称: 第八届武汉电子商务国际会议(The Eighth Wuhan International Conference on E-Business)

会议地点: 武汉

会议语种:英文

页码: 2707-2714

在线出版日期: 2009-05-30（万方平台首次上网日期，不代表论文的发表时间）