An optimization method of estimating parameters in GM (1, 1) model

摘要：

According to Principle of New Information Priority in grey theory, giving the new information larger weight in modeling can improve the effectiveness of gray model. For the GM (1, 1)model has very small samples, and the high overall simulation accuracy does not necessarily guarantee high prediction accuracy, we put forward weighted least square method to estimate parameters in GM (1, 1) model. Focusing on improving the simulation accuracy of new information, focusing on grasping the latest development’ law of things, and aiming at improving the prediction accuracy by giving residual sum of squares of new information larger weight. Finally, we use an example to verify the practicality and reliability of the model.

作者: Li Xue-mei Dang Yao-guo Zhao Jie-jue

作者单位: College of Economics and Management in Nanjing University of Aeronautics &Astronautics Economics and Management in Nanjing University of Aeronautics &Astronautics

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: 448-451

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）