A hybrid model of rough sets and Shannon entropy for building a foreign trade forecasting system

摘要：

Forecasting the volume of foreign trade is important to policy formulation for local governments. This study proposes a machine-learning algorithm as a forecasting tool that is based on Rough sets and Shannon entropy. This study uses historical data from a large municipal to examine the proposed forecasting tool. The results suggest that this tool can be useful in specific trade decisions with unique characteristics and requirements.

关键词： Time scries forecasting model selection rough sets Shannon entropy Expert system combining forecast

作者: Ke Gong Mingwu Liu Yong Fang Xia Zhang

作者单位: School of Management, Chongqing Jiaotong University Chongqing 400074, PR China College of Finance and Economics, Chongqing Jiaotong University Chongqing 400074, PR China

会议类型: 国际会议

会议名称: The Fourth International Joint Conference on Computational Science and Optimization(第四届计算科学与优化国际大会 CSO 2011)

会议地点: 昆明、丽江

会议语种:英文

页码: 7-11

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）