Online Algorithm of Representation for Time-series Based on Polygonal Boundary Reduction Method
Zhu Zhong-ying · Acta Simulata Systematica Sinica · 2003
Time series is an important kind of complex data. Analysis and comparison for polygonal boundary reduction and Douglas-Peucker algorithm for time-series representation are implemented at first. Then, a novel online heuristic algorithm of representation based on polygonal boundary reduction is presented in detail. In this algorithm, the sliding window idea has been used for reference. The quality of approximation is as good as polygonal boundary reduction, and it can process the data online in a constant buffer. The number of segments is automatic computed due to the inherent heuristic searching which is based on the allowed maximum error. Higher quality of approximation is accomplished in simulation on stochastic time-series, and also lower computing complexity does.