Oil Price Forecasting Based on Self-organizing Data Mining

摘要：

The fluctuation of oil prices attracts the great attention of the world. However, the prediction of oil prices is very difficult because the oil price system is so complex. In this paper, AR-GMDH algorithm and AC algorithm are adopted to forecast oil prices. The validity and feasibility of self-organizing data mining are manifested by the comparisons of the prediction result with that of conventional statistical methods. The result shows that self-organizing data mining is a precise method to forecast such complex systems.

作者: Yao Yi Ni Qin

作者单位: College of Mathematics Science, Nanjing Normal University and College of Economics and Management, N College of Economics and Management, Nanjing University of Aeronautics and Astronautics Jiangsu, Nan

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Grey System and Intelligent Services(2009 IEEE灰色系统与服务科学国际会议)

会议地点: 南京

会议语种:英文

页码: 1386-1390

在线出版日期: 2009-10-20（万方平台首次上网日期，不代表论文的发表时间）