Electricity Load Forecasting Using Auto-Regressive and Artificial Neural Network Model
| but.event.date | 28.04.2016 | cs |
| but.event.title | Student EEICT 2016 | cs |
| dc.contributor.author | Vyčítal, Václav | |
| dc.date.accessioned | 2018-07-10T12:48:18Z | |
| dc.date.available | 2018-07-10T12:48:18Z | |
| dc.date.issued | 2016 | cs |
| dc.description.abstract | In this paper a short review of two forecasting models Autoregressive and Artificial neural network is presented. Both models were used to demonstrate its superior performance in load forecasting issues. In the third section the results of load forecasting experiment are given. For obtained forecasted results mean absolute percentage error for autoregressive model was 0.644 % and for artificial neural network model 2.31 %. In this paper error distribution for both models is also shown. | en |
| dc.format | text | cs |
| dc.format.extent | 472-476 | cs |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Proceedings of the 22nd Conference STUDENT EEICT 2016. s. 472-476. ISBN 978-80-214-5350-0 | cs |
| dc.identifier.isbn | 978-80-214-5350-0 | |
| dc.identifier.uri | http://hdl.handle.net/11012/83978 | |
| dc.language.iso | en | cs |
| dc.publisher | Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
| dc.relation.ispartof | Proceedings of the 22nd Conference STUDENT EEICT 2016 | en |
| dc.relation.uri | http://www.feec.vutbr.cz/EEICT/ | cs |
| dc.rights | © Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
| dc.rights.access | openAccess | en |
| dc.subject | Load | en |
| dc.subject | load forecast | en |
| dc.subject | load prediction | en |
| dc.subject | autoregressive model | en |
| dc.subject | artificial neural network | en |
| dc.title | Electricity Load Forecasting Using Auto-Regressive and Artificial Neural Network Model | en |
| dc.type.driver | conferenceObject | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |
| eprints.affiliatedInstitution.department | Fakulta elektrotechniky a komunikačních technologií | cs |
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