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Hybrid artificial neural network with artificial bee colony algorithm for crime classification

Crime prevention is an important roles in police system for any country. Crime classification is one of the components in crime prevention. In this study, we proposed a hybrid crime classification model by combining Artificial Neural Network (ANN) and Artificial Bee Colony (ABC) algorithm (codename...

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Main Authors: Anuar, Syahid, Selamat, Ali, Sallehuddin, Roselina
Format: Article
Published: Springer 2015
Subjects:
T Technology (General)
Online Access:http://eprints.utm.my/id/eprint/59305/
http://dx.doi.org/10.1007/978-3-319-13153-5_4
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spelling my.utm.593052021-12-07T03:55:07Z http://eprints.utm.my/id/eprint/59305/ Hybrid artificial neural network with artificial bee colony algorithm for crime classification Anuar, Syahid Selamat, Ali Sallehuddin, Roselina T Technology (General) Crime prevention is an important roles in police system for any country. Crime classification is one of the components in crime prevention. In this study, we proposed a hybrid crime classification model by combining Artificial Neural Network (ANN) and Artificial Bee Colony (ABC) algorithm (codename ANN-ABC). The idea is by using ABC as a learning mechanism for ANN to overcome the ANN’s local optima problem thus produce more significant results. The ANN-ABC is applied to Communities and Crime dataset to predict ’Crime Categories’. The dataset was collected from UCI machine learning repository. The result of ANN-ABC will be compare with other classification algorithms. The experiment results show that ANN-ABC outperform other algorithms and achieved 86.48% accuracy with average 7% improvement compare to other algorithms. Springer 2015 Article PeerReviewed Anuar, Syahid and Selamat, Ali and Sallehuddin, Roselina (2015) Hybrid artificial neural network with artificial bee colony algorithm for crime classification. Advances in Intelligent Systems and Computing, 331 . pp. 31-40. ISSN 2194-5357 http://dx.doi.org/10.1007/978-3-319-13153-5_4
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Anuar, Syahid
Selamat, Ali
Sallehuddin, Roselina
Hybrid artificial neural network with artificial bee colony algorithm for crime classification
description Crime prevention is an important roles in police system for any country. Crime classification is one of the components in crime prevention. In this study, we proposed a hybrid crime classification model by combining Artificial Neural Network (ANN) and Artificial Bee Colony (ABC) algorithm (codename ANN-ABC). The idea is by using ABC as a learning mechanism for ANN to overcome the ANN’s local optima problem thus produce more significant results. The ANN-ABC is applied to Communities and Crime dataset to predict ’Crime Categories’. The dataset was collected from UCI machine learning repository. The result of ANN-ABC will be compare with other classification algorithms. The experiment results show that ANN-ABC outperform other algorithms and achieved 86.48% accuracy with average 7% improvement compare to other algorithms.
format Article
author Anuar, Syahid
Selamat, Ali
Sallehuddin, Roselina
author_facet Anuar, Syahid
Selamat, Ali
Sallehuddin, Roselina
author_sort Anuar, Syahid
title Hybrid artificial neural network with artificial bee colony algorithm for crime classification
title_short Hybrid artificial neural network with artificial bee colony algorithm for crime classification
title_full Hybrid artificial neural network with artificial bee colony algorithm for crime classification
title_fullStr Hybrid artificial neural network with artificial bee colony algorithm for crime classification
title_full_unstemmed Hybrid artificial neural network with artificial bee colony algorithm for crime classification
title_sort hybrid artificial neural network with artificial bee colony algorithm for crime classification
publisher Springer
publishDate 2015
url http://eprints.utm.my/id/eprint/59305/
http://dx.doi.org/10.1007/978-3-319-13153-5_4
_version_ 1718926042272366592
score 13.211869

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