DC Field | Value | Language |
dc.contributor.author | Užupytė, Rūta | - |
dc.contributor.author | Krilavičius, Tomas | - |
dc.coverage.spatial | LT | - |
dc.date.accessioned | 2017-04-19T06:56:31Z | - |
dc.date.available | 2017-04-19T06:56:31Z | - |
dc.date.issued | 2014 | - |
dc.identifier.issn | 18225934 | - |
dc.identifier.other | VDU02-000016696 | - |
dc.identifier.uri | https://eltalpykla.vdu.lt/1/34338 | - |
dc.description.abstract | 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 | en |
dc.description.sponsorship | Baltijos pažangių technologijų institutas | - |
dc.description.sponsorship | Baltijos pažangių technologijų institutas, Vilnius | - |
dc.description.sponsorship | Informatikos fakultetas | - |
dc.description.sponsorship | Vytauto Didžiojo universitetas | - |
dc.format.extent | p. 68-73 | - |
dc.language.iso | en | - |
dc.relation.ispartof | 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) | - |
dc.rights | Sutarties data 2015-01-07, nr. B000076, laisvai prieinamas internete | lt_LT |
dc.subject | Ontologijos | lt |
dc.subject | Daugiakalbiai dokumentai | lt |
dc.subject | Orders prediction | en |
dc.subject | Time series | en |
dc.subject.classification | Straipsnis recenzuojamoje Lietuvos tarptautinės konferencijos medžiagoje / Article in peer-reviewed Lithuanian international conference proceedings (P1e) | - |
dc.subject.other | Informatika / Informatics (N009) | - |
dc.title | Orders prediction for small IT company | en |
dc.type | research article | - |
dcterms.bibliographicCitation | 12 | - |
dc.date.updated | 2020-04-02T11:13Z | - |
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local.type | P | - |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
crisitem.author.dept | Matematikos ir statistikos katedra | - |
crisitem.author.dept | Taikomosios informatikos katedra | - |
Appears in Collections: | 3. Konferencijų medžiaga / Conference materials Universiteto mokslo publikacijos / University Research Publications
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