A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed...

Full description

Bibliographic Details
Main Authors:	Goudarzi, Shidrokh, Hassan, Wan Haslina, Hassan Abdalla Hashim, Aisha, Soleymani, Seyed Ahmad, Anisi, Mohammad Hossein, Zakaria, Omar M.
Format:	Article
Language:	English English English
Published:	plos.org 2016
Subjects:	TK5101 Telecommunication. Including telegraphy, radio, radar, television
Online Access:	http://irep.iium.edu.my/51495/ http://irep.iium.edu.my/51495/ http://irep.iium.edu.my/51495/1/journal.pone.0151355.PDF http://irep.iium.edu.my/51495/3/51495_A_Novel_RSSI_Prediction_Using_Imperialist_Competition_SCOPUS.pdf http://irep.iium.edu.my/51495/6/51495_A%20novel%20RSSI%20prediction_WOS.pdf

id	iium-51495
recordtype	eprints
spelling	iium-514952017-10-20T14:42:52Z http://irep.iium.edu.my/51495/ A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks Goudarzi, Shidrokh Hassan, Wan Haslina Hassan Abdalla Hashim, Aisha Soleymani, Seyed Ahmad Anisi, Mohammad Hossein Zakaria, Omar M. TK5101 Telecommunication. Including telegraphy, radio, radar, television This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model’s performance, we measured the coefficient of determination (R2 ), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF–FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF–FFA model can be applied as an efficient technique for the accurate prediction of vertical handover. plos.org 2016-07-20 Article PeerReviewed application/pdf en http://irep.iium.edu.my/51495/1/journal.pone.0151355.PDF application/pdf en http://irep.iium.edu.my/51495/3/51495_A_Novel_RSSI_Prediction_Using_Imperialist_Competition_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/51495/6/51495_A%20novel%20RSSI%20prediction_WOS.pdf Goudarzi, Shidrokh and Hassan, Wan Haslina and Hassan Abdalla Hashim, Aisha and Soleymani, Seyed Ahmad and Anisi, Mohammad Hossein and Zakaria, Omar M. (2016) A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks. PLOS ONE, 11 (7). e0151355-1. ISSN 1932-6203 http://dx.doi.org/10.1371/journal.pone.0151355
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English English
topic	TK5101 Telecommunication. Including telegraphy, radio, radar, television
spellingShingle	TK5101 Telecommunication. Including telegraphy, radio, radar, television Goudarzi, Shidrokh Hassan, Wan Haslina Hassan Abdalla Hashim, Aisha Soleymani, Seyed Ahmad Anisi, Mohammad Hossein Zakaria, Omar M. A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks
description	This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model’s performance, we measured the coefficient of determination (R2 ), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF–FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF–FFA model can be applied as an efficient technique for the accurate prediction of vertical handover.
format	Article
author	Goudarzi, Shidrokh Hassan, Wan Haslina Hassan Abdalla Hashim, Aisha Soleymani, Seyed Ahmad Anisi, Mohammad Hossein Zakaria, Omar M.
author_facet	Goudarzi, Shidrokh Hassan, Wan Haslina Hassan Abdalla Hashim, Aisha Soleymani, Seyed Ahmad Anisi, Mohammad Hossein Zakaria, Omar M.
author_sort	Goudarzi, Shidrokh
title	A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks
title_short	A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks
title_full	A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks
title_fullStr	A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks
title_full_unstemmed	A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks
title_sort	novel rssi prediction using imperialist competition algorithm (ica), radial basis function (rbf) and firefly algorithm (ffa) in wireless networks
publisher	plos.org
publishDate	2016
url	http://irep.iium.edu.my/51495/ http://irep.iium.edu.my/51495/ http://irep.iium.edu.my/51495/1/journal.pone.0151355.PDF http://irep.iium.edu.my/51495/3/51495_A_Novel_RSSI_Prediction_Using_Imperialist_Competition_SCOPUS.pdf http://irep.iium.edu.my/51495/6/51495_A%20novel%20RSSI%20prediction_WOS.pdf
first_indexed	2023-09-18T21:12:54Z
last_indexed	2023-09-18T21:12:54Z
_version_	1777411371244191744

A novel RSSI prediction using imperialist competition algorithm (ICA), radial basis function (RBF) and firefly algorithm (FFA) in wireless networks

Similar Items