Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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An Adaption of Pattern Sequence-based Electricity Load Forecasting with Match Filtering

  • Chu, Fazheng (Economics and Management College of Qingdao Agricultural University) ;
  • Jung, Sung-Hwan (Dept. of Computer Engineering, Changwon National University)
  • Received : 2017.02.20
  • Accepted : 2017.04.08
  • Published : 2017.05.31
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Abstract

The Pattern Sequence-based Forecasting (PSF) is an approach to forecast the behavior of time series based on similar pattern sequences. The innovation of PSF method is to convert the load time series into a label sequence by clustering technique in order to lighten computational burden. However, it brings about a new problem in determining the number of clusters and it is subject to insufficient similar days occasionally. In this paper we proposed an adaption of the PSF method, which introduces a new clustering index to determine the number of clusters and imposes a threshold to solve the problem caused by insufficient similar days. Our experiments showed that the proposed method reduced the mean absolute percentage error (MAPE) about 15%, compared to the PSF method.

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References

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