A hybrid model of rough sets and Shannon entropy for building a foreign trade forecasting system
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.
Time scries forecasting model selection rough sets Shannon entropy Expert system combining forecast
Ke Gong Mingwu Liu Yong Fang Xia Zhang
School of Management, Chongqing Jiaotong University Chongqing 400074, PR China College of Finance and Economics, Chongqing Jiaotong University Chongqing 400074, PR China
国际会议
昆明、丽江
英文
7-11
2011-04-15(万方平台首次上网日期,不代表论文的发表时间)