Use this url to cite publication: https://hdl.handle.net/20.500.12259/34338
Orders prediction for small IT company
Type of publication
Straipsnis recenzuojamoje Lietuvos tarptautinės konferencijos medžiagoje / Article in peer-reviewed Lithuanian international conference proceedings (P1e)
Author(s)
| Author | Affiliation | |||
|---|---|---|---|---|
LT | Baltijos pažangių technologijų institutas, Vilnius | LT | ||
Baltijos pažangių technologijų institutas | LT |
Title
Orders prediction for small IT company
Is part of
ECT-2014 : Electrical and control technologies : proceedings of the 9th international conference on electrical and control technologies, May 8-9, 2014, Kaunas, Lithuania. Kaunas : Technologija, 9 (2014)
Date Issued
| Date |
|---|
2014 |
Publisher
Kaunas : Technologija
Extent
p. 68-73
Abstract (en)
Reliable methodology for service orders prediction can significantly improve the quality of business strategy. It is very important to identify the seasonal behavior in order data to correctly predict customer demand and make appropriate business decisions. There are several methods to model and forecast time series with seasonal pattern. This paper compares seasonal naive, Holt – Winters seasonal, SARIMA and neural networks methods in order to evaluate their performance in prediction of the future values of time series that consist of the monthly orders in a small IT company.
Type of document
type::text::journal::journal article::research article
Language
Anglų / English (en)
Coverage Spatial
Lietuva / Lithuania (LT)
ISSN (of the container)
1822-5934
Other Identifier(s)
VDU02-000016696
Access Rights
Atviroji prieiga / Open Access