Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)

SIMFAC-A New Forecasting Method for Sporadic Time Series

Authors
Klaus Spicher, Boxing Li, Dianjun Fang
Corresponding Author
Dianjun Fang
Available Online April 2019.
DOI
https://doi.org/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 Then the focus is laid on the analysis and presentation of a new forecasting yet unpublished method, SIMFAC (1), which is dedicated to STS and includes a new error metric, MEM (Matching Event Metric).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.
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Proceedings
3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
Part of series
Advances in Computer Science Research
Publication Date
April 2019
ISBN
978-94-6252-708-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmeit-19.2019.48How to use a DOI?
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  -