Abstract:
Based on analyzing the relation of data points in time series, a novel series segmenting algorithm based on triangular midline is presented. During scanning these temporal data, this approach chooses three continuous data points in turn and calculates the triangle’s midline. According to these values and the user-defined distance threshold, this method records important turning points reflecting the sequence’s feature. Using these key points, the original time series is segmented and fitted linearly. Experimental results show that the new method is effective.
Key words:
data series,
linear fitting,
turning points,
triangular midline
摘要: 从石油测井数据解释的实际应用需求出发,提出一种新的基于三角形中线的数据序列分段算法。在扫描数据的过程中依次计算 3个连续数据形成的三角形中线长度,根据自定义的中线长度阈值选择反映序列趋势变化的关键转折点,实现数据序列的线性拟合。实验结果表明该算法具有良好的拟合质量和较高的效率。
关键词:
数据序列,
线性拟合,
转折点,
三角形中线
CLC Number:
DU Yi; LU De-tang; LI Dao-lun; ZHANG Ting;. Data Series Linear Fitting Algorithm Based on Triangular Midline[J]. Computer Engineering, 2008, 34(13): 21-23.
杜 奕;卢德唐;李道伦;张 挺;. 基于三角形中线的数据序列线性拟合算法[J]. 计算机工程, 2008, 34(13): 21-23.