SIMFAC-A New Forecasting Method for Sporadic Time Series
- Klaus Spicher, Boxing Li, Dianjun Fang
- Corresponding Author
- Dianjun Fang
Available Online April 2019.
- https://doi.org/10.2991/icmeit-19.2019.48How to use a DOI?
- Sporadic data; Forecasting methods; Croston; SIMFAC; Error Metrics.
- This essay relates mainly to sporadic FC (forecasting) methods and error measures. The existing related FC methods of sporadic time series (STS), including the SES (Simple Exponential Smoothing), Croston’ s / SBA method and patented WSS method as well as two applicable error metrics APE and THEIL'S U are introduced briefly. Then the focus is laid on the analysis and presentation of a new forecasting yet unpublished method, SIMFAC (1), which is dedicated to STS and includes a new error metric, MEM (Matching Event Metric). For a more comprehensive comparison among methods, Cosine Similarity (CS) metric, will be introduced and applied in this essay.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Klaus Spicher AU - Boxing Li AU - Dianjun Fang PY - 2019/04 DA - 2019/04 TI - SIMFAC-A New Forecasting Method for Sporadic Time Series BT - 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019) PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/icmeit-19.2019.48 DO - https://doi.org/10.2991/icmeit-19.2019.48 ID - Spicher2019/04 ER -