TY - JOUR
T1 - An optimal online semi-connected PLA algorithm with maximum error bound
AU - Zhao, Huanyu
AU - Pang, Chaoyi
AU - Kotagiri, Ramamohanarao
AU - Pang, Christopher K.
AU - Deng, Ke
AU - Yang, Jian
AU - Li, Tongliang
PY - 2022/1
Y1 - 2022/1
N2 - Piecewise Linear Approximation (PLA) is one of the most widely used approaches for representing a time series with a set of approximated line segments. With this compressed form of representation, many large complicated time series can be efficiently stored, transmitted and analyzed. In this article, with the introduced concept of 'semi-connection' that allowing two representation lines to be connected at a point between two consecutive time stamps, we propose a new optimal linear-time PLA algorithm SemiOptConnAlg for generating the least number of semi-connected line segments with guaranteed maximum error bound. With extended experimental tests, we demonstrate that the proposed algorithm is very efficient in execution time and achieves better performances than the state-of-art solutions.
AB - Piecewise Linear Approximation (PLA) is one of the most widely used approaches for representing a time series with a set of approximated line segments. With this compressed form of representation, many large complicated time series can be efficiently stored, transmitted and analyzed. In this article, with the introduced concept of 'semi-connection' that allowing two representation lines to be connected at a point between two consecutive time stamps, we propose a new optimal linear-time PLA algorithm SemiOptConnAlg for generating the least number of semi-connected line segments with guaranteed maximum error bound. With extended experimental tests, we demonstrate that the proposed algorithm is very efficient in execution time and achieves better performances than the state-of-art solutions.
KW - Bounded error in approximation
KW - Data stream
KW - Online algorithm
KW - Piecewise linear approximation (PLA)
KW - Semi-connected
KW - Time series
UR - http://www.scopus.com/inward/record.url?scp=85121744714&partnerID=8YFLogxK
U2 - 10.1109/TKDE.2020.2981319
DO - 10.1109/TKDE.2020.2981319
M3 - Article
AN - SCOPUS:85121744714
SN - 1041-4347
VL - 34
SP - 164
EP - 177
JO - IEEE Transactions on Knowledge and Data Engineering
JF - IEEE Transactions on Knowledge and Data Engineering
IS - 1
ER -