Please use this identifier to cite or link to this item:
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/33872
Title: | A comprehensive study of crime detection with PCA and different neural network approach |
Authors: | Ahmad Kadri, Junoh Muhammad Naufal, Mansor kadri@unimap.edu.my apairia@yahoo.com |
Keywords: | Crime rate Elman Neural Network Feed Forward Neural Network and Probabilistic Neural Network Principal Component analysis |
Issue Date: | 2013 |
Publisher: | Springer-Verlag |
Citation: | Advances in Intelligent Systems and Computing, vol. 206 AISC, 2013, pages 611-618 |
Abstract: | Crime rate in Malaysia is almost in awareness stage. The centre for Public Policy Studies Malaysia reports that the ratio of police to population is 3.6 officers to 1,000 citizens in Malaysia. This lack of manpower sources ratios alone are not a comprehensive afford of crime fighting capabilities. Thus, dealing with these circumstances, we present a comprehensive study to determine bandit behavior with PCA and different neural network algorithm such as Elman Neural Network (ELMNN), Feed Forward Neural Network (FFNN) and Cascade-Forward Neural Network (CFNN). This system provided a good justification as a monitoring supplementary tool for the Malaysian police arm forced. |
Description: | Link to publisher's homepage at http://link.springer.com/ |
URI: | http://link.springer.com/chapter/10.1007%2F978-3-642-36981-0_56 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33872 |
ISBN: | 978-364236980-3 |
ISSN: | 2194-5357 |
Appears in Collections: | Institute of Engineering Mathematics (Articles) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
A comprehensive study of crime detection with PCA and different neural network approach.pdf | 9.7 kB | Adobe PDF | View/Open |
Items in UniMAP Library Digital Repository are protected by copyright, with all rights reserved, unless otherwise indicated.