A Method for Data Stream Processing Based on Curve Fitting

摘要：

The sampling storage method which used in the current data stream could not respond data tendency effectively. For the problem, this paper presents a new processing method based on curve fitting. A weighted least square principle is used to fit the cached stream data and better model description is obtained. Then the fitting results are analyzed by clustering algorithm, which serves as a classifier for polynomial fitting parameters According to the clustering result, the appropriate window size will be given to fit the periodic stream data. Comparing the function solutions with the actual data, the different methods are adopted to store data according to the comparison result. The experimental results indicate that the proposed method has better fitting accuracy and compression ratio, could meet the requirement of data stream processing. And the data tendency could be responded effectively by the fitting results.

关键词： curve fitting data stream clustering least-square principle

作者: Yixu Song Jing Hu Xiaokui Yang Jie Fu Xiufen Xie

作者单位: State Key Laboratory of Intelligent Technology and System Department of Computer Science and Technol Department of Computer Science and Technology University of Science and Technology Beijing Beijing, Sany Intelligent Control Equipment CO.LTD Changsha, Hunan, China

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 1382-1386

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）