关键词: 分段线性表示, 极值点, 斜率, 拟合误差, 时间序列挖掘

Abstract: In the existing algorithms of piecewise linear representation for time series，local extremum points always are regarded as segment points，but the changement of time series states can’t be depicted completely only by them.So according to the idea of piecewise linear of time series，new segment points are brought in after local extremum points are fixed，which can acquire high fitting precision.The difference of slopes is used to reflect state changements and by comparing with slopes of adjacent sequence segments，new segment points can be confirmed.Lastly this method leads to much less fitting error and better practicability.

Key words: piecewise linear representation, extremum points, slope, fitting error, data mining