Using dynamic neural networks for server load prediction

Simple item page
dc.citation.epage160
dc.citation.spage157
dc.contributor.affiliationLviv Polytechnic National University, Department of Applied mathematics
dc.contributor.authorPukach, Pavlo
dc.contributor.authorHladun, Volodymyr
dc.coverage.placenameLviv
dc.coverage.temporal25-27 June 2018
dc.date.accessioned2018-09-03T11:41:11Z
dc.date.available2018-09-03T11:41:11Z
dc.date.created2018-06-25
dc.date.issued2018-06-25
dc.description.abstractIn this paper, the approach of using neural networks for making time series predictions of strongly nonlinear data is used. A brief examination of neural networks usage for time series predictions is given, as well as the definition and schematics of LSTM blocks. The comparison between the time delay values and the prediction accuracy is given. It is shown that certain values of time delay can greatly increase the prediction accuracy.
dc.format.extent157-160
dc.format.pages4
dc.identifier.citationPukach P. Using dynamic neural networks for server load prediction / Pavlo Pukach, Volodymyr Hladun // Computational linguistics and intelligent systems, 25-27 June 2018. — Lviv : Lviv Polytechnic National University, 2018. — Vol 2 : Workshop. — P. 157–160. — (Section II. Intelligent Systems).
dc.identifier.citationenPukach P. Using dynamic neural networks for server load prediction / Pavlo Pukach, Volodymyr Hladun // Computational linguistics and intelligent systems, 25-27 June 2018. — Lviv : Lviv Polytechnic National University, 2018. — Vol 2 : Workshop. — P. 157–160. — (Section II. Intelligent Systems).
dc.identifier.issn2523-4013
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/42563
dc.language.isoen
dc.publisherLviv Polytechnic National University
dc.relation.ispartofComputational linguistics and intelligent systems (2), 2018
dc.relation.references1. M. Beale, M. Hagan, and H.Demuth, “Matlab neural network toolbox user’s guide,” The Math Works Inc., 2010, http://www.mathworks.com/help/pdfdoc/nnet/nnet ug.pdf.
dc.relation.references2. C. A. Mitrea, C. K. M. Lee, and Z. Wu, “A comparison between neural networks and traditional forecasting methods: A case study,” in International Journal of Engineering Business Management, vol. 1, no. 2 2009, pp. 19–24.
dc.relation.referencesen1. M. Beale, M. Hagan, and H.Demuth, "Matlab neural network toolbox user’s guide," The Math Works Inc., 2010, http://www.mathworks.com/help/pdfdoc/nnet/nnet ug.pdf.
dc.relation.referencesen2. C. A. Mitrea, C. K. M. Lee, and Z. Wu, "A comparison between neural networks and traditional forecasting methods: A case study," in International Journal of Engineering Business Management, vol. 1, no. 2 2009, pp. 19–24.
dc.relation.urihttp://www.mathworks.com/help/pdfdoc/nnet/nnet
dc.rights.holder© 2018 for the individual papers by the papers’ authors. Copying permitted only for private and academic purposes. This volume is published and copyrighted by its editors.
dc.subjectneural networks
dc.subjectlong short-term memory
dc.subjecttime series prediction
dc.titleUsing dynamic neural networks for server load prediction
dc.typeConference Abstract

Files

Original bundle
Now showing 1 - 2 of 2
No Thumbnail Available
Name:
COLINS_2018_2018v2_Pukach_P-Using_dynamic_neural_networks_157-160.pdf
Size:
1.1 MB
Format:
Adobe Portable Document Format
Download
No Thumbnail Available
Name:
COLINS_2018_2018v2_Pukach_P-Using_dynamic_neural_networks_157-160__COVER.png
Size:
249.77 KB
Format:
Portable Network Graphics
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.94 KB
Format:
Plain Text
Description:
Download

Collections

Computational linguistics and intelligent systems. – 2018 р.