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Viability of using ANN-BP on a handheld device

This paper discusses the feasibility of operating an artificial neural network - back propagation (ANN-BP) in a handheld device. Comparisons were done between operating an ANN-BP on a desktop versus a handheld device in duration of time and accuracy. It was found that by implementing an ANN-BP on a...

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Main Authors: Weng L.Y., Omar J.B., Siah Y.K., Abidin I.B.Z., Ahmed S.K.
Other Authors: 26326032700
Format: Conference paper
Published: 2023
Subjects:
ANN-BP
Artificial intelligence
Artificial neural networks
Handheld device
Backpropagation
Hand held computers
Information science
Intelligent computing
Artificial Neural Network
Current processors
Hand held device
Processing Time
Neural networks
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id my.uniten.dspace-30573
record_format dspace
spelling my.uniten.dspace-305732023-12-29T15:49:38Z Viability of using ANN-BP on a handheld device Weng L.Y. Omar J.B. Siah Y.K. Abidin I.B.Z. Ahmed S.K. 26326032700 24463418200 24448864400 35606640500 25926812900 ANN-BP Artificial intelligence Artificial neural networks Handheld device Backpropagation Hand held computers Information science Intelligent computing ANN-BP Artificial Neural Network Current processors Hand held device Processing Time Neural networks This paper discusses the feasibility of operating an artificial neural network - back propagation (ANN-BP) in a handheld device. Comparisons were done between operating an ANN-BP on a desktop versus a handheld device in duration of time and accuracy. It was found that by implementing an ANN-BP on a handheld device, the speed was slower as compared to running on a desktop. The accuracy of results did not differ much based on the device the ANN-BP was executed upon. As a conclusion, the viability of using a handheld device to run ANN-BP is not practical with current processor speeds as the processing time is approximately 300 times longer than that of a desktop. � 2010 IEEE. Final 2023-12-29T07:49:38Z 2023-12-29T07:49:38Z 2010 Conference paper 10.1109/ICICCI.2010.82 2-s2.0-77958502587 https://www.scopus.com/inward/record.uri?eid=2-s2.0-77958502587&doi=10.1109%2fICICCI.2010.82&partnerID=40&md5=4f3a2d1f0011132d71fdb3acd3737730 https://irepository.uniten.edu.my/handle/123456789/30573 5566012 149 151 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic ANN-BP
Artificial intelligence
Artificial neural networks
Handheld device
Backpropagation
Hand held computers
Information science
Intelligent computing
ANN-BP
Artificial Neural Network
Current processors
Hand held device
Processing Time
Neural networks
spellingShingle ANN-BP
Artificial intelligence
Artificial neural networks
Handheld device
Backpropagation
Hand held computers
Information science
Intelligent computing
ANN-BP
Artificial Neural Network
Current processors
Hand held device
Processing Time
Neural networks
Weng L.Y.
Omar J.B.
Siah Y.K.
Abidin I.B.Z.
Ahmed S.K.
Viability of using ANN-BP on a handheld device
description This paper discusses the feasibility of operating an artificial neural network - back propagation (ANN-BP) in a handheld device. Comparisons were done between operating an ANN-BP on a desktop versus a handheld device in duration of time and accuracy. It was found that by implementing an ANN-BP on a handheld device, the speed was slower as compared to running on a desktop. The accuracy of results did not differ much based on the device the ANN-BP was executed upon. As a conclusion, the viability of using a handheld device to run ANN-BP is not practical with current processor speeds as the processing time is approximately 300 times longer than that of a desktop. � 2010 IEEE.
author2 26326032700
author_facet 26326032700
Weng L.Y.
Omar J.B.
Siah Y.K.
Abidin I.B.Z.
Ahmed S.K.
format Conference paper
author Weng L.Y.
Omar J.B.
Siah Y.K.
Abidin I.B.Z.
Ahmed S.K.
author_sort Weng L.Y.
title Viability of using ANN-BP on a handheld device
title_short Viability of using ANN-BP on a handheld device
title_full Viability of using ANN-BP on a handheld device
title_fullStr Viability of using ANN-BP on a handheld device
title_full_unstemmed Viability of using ANN-BP on a handheld device
title_sort viability of using ann-bp on a handheld device
publishDate 2023
_version_ 1806426471004110848
score 13.222552

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