An optimal online semi-connected PLA algorithm with maximum error bound

Huanyu Zhao, Chaoyi Pang*, Ramamohanarao Kotagiri, Christopher K. Pang, Ke Deng, Jian Yang, Tongliang Li*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)164-177
Number of pages14
JournalIEEE Transactions on Knowledge and Data Engineering
Issue number1
Publication statusPublished - Jan 2022


  • Bounded error in approximation
  • Data stream
  • Online algorithm
  • Piecewise linear approximation (PLA)
  • Semi-connected
  • Time series


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