https://oldena.lpnu.ua/handle/ntb/42563| Title: | Using dynamic neural networks for server load prediction |
| Authors: | Pukach, Pavlo Hladun, Volodymyr |
| Affiliation: | Lviv Polytechnic National University, Department of Applied mathematics |
| Bibliographic description (Ukraine): | Pukach 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). |
| Bibliographic description (International): | Pukach 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). |
| Is part of: | Computational linguistics and intelligent systems (2), 2018 |
| Issue Date: | 25-Jun-2018 |
| Publisher: | Lviv Polytechnic National University |
| Place of the edition/event: | Lviv |
| Temporal Coverage: | 25-27 June 2018 |
| Keywords: | neural networks long short-term memory time series prediction |
| Number of pages: | 4 |
| Page range: | 157-160 |
| Start page: | 157 |
| End page: | 160 |
| Abstract: | In 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. |
| URI: | https://ena.lpnu.ua/handle/ntb/42563 |
| ISSN: | 2523-4013 |
| Copyright owner: | © 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. |
| URL for reference material: | http://www.mathworks.com/help/pdfdoc/nnet/nnet |
| References (Ukraine): | 1. 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. 2. 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. |
| References (International): | 1. 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. 2. 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. |
| Content type: | Conference Abstract |
| Appears in Collections: | Computational linguistics and intelligent systems. – 2018 р. |
| File | Description | Size | Format | |
|---|---|---|---|---|
| COLINS_2018_2018v2_Pukach_P-Using_dynamic_neural_networks_157-160.pdf | 1.13 MB | Adobe PDF | View/Open | |
| COLINS_2018_2018v2_Pukach_P-Using_dynamic_neural_networks_157-160__COVER.png | 249.77 kB | image/png | View/Open |
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