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Reseach Article

Mobility Prediction using Modified RBF Network

by Mohammad F. Hassanin, Amr Badr
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 118 - Number 25
Year of Publication: 2015
Authors: Mohammad F. Hassanin, Amr Badr
10.5120/20959-3410

Mohammad F. Hassanin, Amr Badr . Mobility Prediction using Modified RBF Network. International Journal of Computer Applications. 118, 25 ( May 2015), 1-4. DOI=10.5120/20959-3410

@article{ 10.5120/20959-3410,
author = { Mohammad F. Hassanin, Amr Badr },
title = { Mobility Prediction using Modified RBF Network },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 118 },
number = { 25 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume118/number25/20959-3410/ },
doi = { 10.5120/20959-3410 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:02:37.797049+05:30
%A Mohammad F. Hassanin
%A Amr Badr
%T Mobility Prediction using Modified RBF Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 118
%N 25
%P 1-4
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recently, with the wide increase use of mobile devices, users are using it to achieve different types of tasks like multimedia and internet services. Many studies have been introduced to identify user's behaviors. The most common factor is the location. By knowing user's locations, set of required tasks can be provided for user. Mobility prediction is to predict the user's next location while moving. The recent advances in mobile phones like Global Positioning System (GPS) make it much easier to achieve such tasks. In this paper, modified Radial Basis Function Networks (RBF Network) algorithm is developed to predict user's locations. Proposed approach depend on clustering data using DBCLUM then using backpropagation algorithm for classifying data in on time using RBF Network. Experiment applied using weka 3. 6 on Geolife dataset. Finally, prediction accuracy reported as 90%.

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Index Terms

Computer Science
Information Sciences

Keywords

Mobility Prediction Neural Network GPS Location Based Service.