Wireless user estimation using artificial neural networks

© 2015 IEEE. Mobile devices, with the improving trend of smartphone use, is an area of study for human behavior on wireless data communications systems which serves as the converging focal point. The prediction of user quantities with non-intrusive data gathering in wireless communications trends an...

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Main Authors:	Abinoja, Daniel, Bedruz, Rhen Anjerome, Jovellanos, Kevin Loo, Bandala, Argel A.
Format:	text
Published:	Animo Repository 2016
Online Access:	https://animorepository.dlsu.edu.ph/faculty_research/748 https://animorepository.dlsu.edu.ph/context/faculty_research/article/1747/type/native/viewcontent
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Institution:	De La Salle University

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spelling	oai:animorepository.dlsu.edu.ph:faculty_research-17472023-01-09T09:21:03Z Wireless user estimation using artificial neural networks Abinoja, Daniel Bedruz, Rhen Anjerome Jovellanos, Kevin Loo Bandala, Argel A. © 2015 IEEE. Mobile devices, with the improving trend of smartphone use, is an area of study for human behavior on wireless data communications systems which serves as the converging focal point. The prediction of user quantities with non-intrusive data gathering in wireless communications trends and the correlation of Wi-Fi characteristics with quantity are important links towards data aggregation technique developments. To estimate user load in wireless connection systems, multi-layer feed forward artificial neural network based on BP algorithm is proposed and implemented with MATLAB to aid in optimization of performance in such networks. Error calculation, test, validation, and training performance are evaluated for the algorithm's applicability. 2016-01-25T08:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/748 https://animorepository.dlsu.edu.ph/context/faculty_research/article/1747/type/native/viewcontent Faculty Research Work Animo Repository
institution	De La Salle University
building	De La Salle University Library
continent	Asia
country	Philippines Philippines
content_provider	De La Salle University Library
collection	DLSU Institutional Repository
description	© 2015 IEEE. Mobile devices, with the improving trend of smartphone use, is an area of study for human behavior on wireless data communications systems which serves as the converging focal point. The prediction of user quantities with non-intrusive data gathering in wireless communications trends and the correlation of Wi-Fi characteristics with quantity are important links towards data aggregation technique developments. To estimate user load in wireless connection systems, multi-layer feed forward artificial neural network based on BP algorithm is proposed and implemented with MATLAB to aid in optimization of performance in such networks. Error calculation, test, validation, and training performance are evaluated for the algorithm's applicability.
format	text
author	Abinoja, Daniel Bedruz, Rhen Anjerome Jovellanos, Kevin Loo Bandala, Argel A.
spellingShingle	Abinoja, Daniel Bedruz, Rhen Anjerome Jovellanos, Kevin Loo Bandala, Argel A. Wireless user estimation using artificial neural networks
author_facet	Abinoja, Daniel Bedruz, Rhen Anjerome Jovellanos, Kevin Loo Bandala, Argel A.
author_sort	Abinoja, Daniel
title	Wireless user estimation using artificial neural networks
title_short	Wireless user estimation using artificial neural networks
title_full	Wireless user estimation using artificial neural networks
title_fullStr	Wireless user estimation using artificial neural networks
title_full_unstemmed	Wireless user estimation using artificial neural networks
title_sort	wireless user estimation using artificial neural networks
publisher	Animo Repository
publishDate	2016
url	https://animorepository.dlsu.edu.ph/faculty_research/748 https://animorepository.dlsu.edu.ph/context/faculty_research/article/1747/type/native/viewcontent
_version_	1754713721713721344

Wireless user estimation using artificial neural networks

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