Educational bandwidth traffic prediction using non-linear autoregressive neural networks
Time series network traffic analysis and forecasting are important for fundamental to many decision-making processes, also to understand network performance, reliability and security, as well as to identify potential problems. This paper provides the latest work on London South Bank University (LSBU...
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| Altri autori: | , , |
| Natura: | article |
| Lingua: | spagnolo |
| Pubblicazione: |
2018
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| Accesso online: | http://revistas.utp.ac.pa/index.php/memoutp/article/view/1919 http://ridda2.utp.ac.pa/handle/123456789/5763 |
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| _version_ | 1869652457530851328 |
|---|---|
| author | Dyllon, Shwan |
| author2 | Hong, Timothy Oumar, Ousmane Abdoulaye Xiao, Perry |
| author2_role | author author author |
| author_browse | Dyllon, Shwan Hong, Timothy Oumar, Ousmane Abdoulaye Xiao, Perry |
| author_facet | Dyllon, Shwan Hong, Timothy Oumar, Ousmane Abdoulaye Xiao, Perry |
| author_role | author |
| collection | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| dc.contributor.none.fl_str_mv | |
| dc.creator.none.fl_str_mv | Dyllon, Shwan Hong, Timothy Oumar, Ousmane Abdoulaye Xiao, Perry |
| dc.date.none.fl_str_mv | 2018-09-30 2018-12-04T14:32:11Z 2018-12-04T14:32:11Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://revistas.utp.ac.pa/index.php/memoutp/article/view/1919 http://ridda2.utp.ac.pa/handle/123456789/5763 |
| dc.language.none.fl_str_mv | spa |
| dc.publisher.none.fl_str_mv | Universidad Tecnológica de Panamá |
| dc.relation.none.fl_str_mv | http://revistas.utp.ac.pa/index.php/memoutp/article/view/1919/2861 |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/4.0/ |
| dc.source.none.fl_str_mv | Memorias de Congresos UTP; 2018: The 21st International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines - CLAWAR 2018; 251-261 reponame:Repositorio Institucional de documento digitales de acceso abierto de la UTP instname:Universidad Tecnológica de Panamá instacron:U Tecnológica de Panamá |
| dc.subject.none.fl_str_mv | Educational bandwidth;traffic prediction |
| dc.title.none.fl_str_mv | Educational bandwidth traffic prediction using non-linear autoregressive neural networks |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| description | Time series network traffic analysis and forecasting are important for fundamental to many decision-making processes, also to understand network performance, reliability and security, as well as to identify potential problems. This paper provides the latest work on London South Bank University (LSBU) network data traffic analysis by adapting nonlinear autoregressive exogenous model (NARX) based on Levenberg-Marquardt backpropagation algorithm. This technique can analyse and predict data usage in its current and future states, as well as visualise the hourly, daily, weekly, monthly, and quarterly activities with less computation requirement. Results and analysis proved the accuracy of the prediction techniques. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | lrtest_21f342c915ddea30005a3c0193bd5d87 |
| instacron_str | U Tecnológica de Panamá |
| institution | U Tecnológica de Panamá |
| instname_str | Universidad Tecnológica de Panamá |
| language | spa |
| network_acronym_str | lrtest |
| network_name_str | lr |
| oai_identifier_str | oai:ridda2.utp.ac.pa:123456789/5763 |
| publishDate | 2018 |
| publishDateSort | 2018 |
| publisher.none.fl_str_mv | Universidad Tecnológica de Panamá |
| reponame_str | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | https://creativecommons.org/licenses/by-nc-sa/4.0/ |
| spelling | Educational bandwidth traffic prediction using non-linear autoregressive neural networksDyllon, ShwanHong, TimothyOumar, Ousmane AbdoulayeXiao, PerryEducational bandwidth;traffic predictionTime series network traffic analysis and forecasting are important for fundamental to many decision-making processes, also to understand network performance, reliability and security, as well as to identify potential problems. This paper provides the latest work on London South Bank University (LSBU) network data traffic analysis by adapting nonlinear autoregressive exogenous model (NARX) based on Levenberg-Marquardt backpropagation algorithm. This technique can analyse and predict data usage in its current and future states, as well as visualise the hourly, daily, weekly, monthly, and quarterly activities with less computation requirement. Results and analysis proved the accuracy of the prediction techniques.Universidad Tecnológica de Panamá2018-09-302018-12-04T14:32:11Z2018-12-04T14:32:11Zinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://revistas.utp.ac.pa/index.php/memoutp/article/view/1919http://ridda2.utp.ac.pa/handle/123456789/5763Memorias de Congresos UTP; 2018: The 21st International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines - CLAWAR 2018; 251-261reponame:Repositorio Institucional de documento digitales de acceso abierto de la UTPinstname:Universidad Tecnológica de Panamáinstacron:U Tecnológica de Panamáspahttp://revistas.utp.ac.pa/index.php/memoutp/article/view/1919/2861info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/4.0/oai:ridda2.utp.ac.pa:123456789/57632019-11-29T17:34:16Z |
| spellingShingle | Educational bandwidth traffic prediction using non-linear autoregressive neural networks Dyllon, Shwan Educational bandwidth;traffic prediction |
| status_str | publishedVersion |
| title | Educational bandwidth traffic prediction using non-linear autoregressive neural networks |
| title_full | Educational bandwidth traffic prediction using non-linear autoregressive neural networks |
| title_fullStr | Educational bandwidth traffic prediction using non-linear autoregressive neural networks |
| title_full_unstemmed | Educational bandwidth traffic prediction using non-linear autoregressive neural networks |
| title_short | Educational bandwidth traffic prediction using non-linear autoregressive neural networks |
| title_sort | Educational bandwidth traffic prediction using non-linear autoregressive neural networks |
| topic | Educational bandwidth;traffic prediction |
| url | http://revistas.utp.ac.pa/index.php/memoutp/article/view/1919 http://ridda2.utp.ac.pa/handle/123456789/5763 |