SIMFAC-A New Forecasting Method for Sporadic Time Series

DOI

10.2991/icmeit-19.2019.48How to use a DOI?

Keywords

Sporadic data; Forecasting methods; Croston; SIMFAC; Error Metrics.

Abstract

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 Then the focus is laid on the analysis and presentation of a new forecasting yet unpublished method, SIMFAC (1), which is dedicated to STS and includes a new error metric, MEM (Matching Event Metric).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.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
PB  - Atlantis Press
SP  - 275
EP  - 283
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.48
DO  - 10.2991/icmeit-19.2019.48
ID  - Spicher2019/04
ER  -