RESEARCH AND APPLICATION OF PIECEWISE LINEAR FITTING ALGORITHM BASED ON STOCK TIME SERIES
This paper discusses an Improved Linear Fitting Algorithm Based on Stock Time Series (SPLR).Firstly, the algorithm defines a set of stock trend points and traversals the stocks time series, and finds the stock trend points by extremes method and the investors experience threshold value.Then it finds the important trend point by the difference of the slope of triangle edge.Finally, connecting these trend points which are found by the above method to present piecewise linear of the stocks time series. This papers experiment compares with several other fitting algorithms and computes the errors, and the results show: this method is more suitable for fitting the stock and has better timing results, and in large data compression it also can express the stock trend better.
stock time series data compression piecewise linear fitting important trend points security predict
WEIHONG WANG XIANGBIN ZHENG SONG WANG ZHAOLIN FANG CHUNPING WANG
Dept. of Computer Science Zhejiang University of Technology Hangzhou
国际会议
成都
英文
2005-2009
2011-11-25（万方平台首次上网日期，不代表论文的发表时间）