Anomaly detection in vessel tracking using Support Vector Machines (SVMs)
The paper is devoted to supervise method approach to identify the vessel anomaly behavior in waterways using the Automated Identification System (AIS) vessel reporting data. In this work, we describe the use of SVMs to detect the vessel anomaly behavior. The SVMs is a supervised method that needs so...
| Main Authors: | , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/35362/ http://irep.iium.edu.my/35362/1/asadullah.pdf |
| _version_ | 1848781042816647168 |
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| author | Dwi Handayani, Dini Oktarina Sediono, Wahju Shah, Asadullah |
| author_facet | Dwi Handayani, Dini Oktarina Sediono, Wahju Shah, Asadullah |
| author_sort | Dwi Handayani, Dini Oktarina |
| building | IIUM Repository |
| collection | Online Access |
| description | The paper is devoted to supervise method approach to identify the vessel anomaly behavior in waterways using the Automated Identification System (AIS) vessel reporting data. In this work, we describe the use of SVMs to detect the vessel anomaly behavior. The SVMs is a supervised method that needs some pre knowledge to extract the maritime movement patterns of AIS raw data into information. This is the basis to remodel information into a meaningful and valuable form. The result of this work shows that the SVMs technique is applicable to be used for the identification of vessel anomaly behavior. It is proved that the best accuracy result is obtained from dividing raw data into 70% for training and 30% for testing stages. |
| first_indexed | 2025-11-14T15:43:17Z |
| format | Proceeding Paper |
| id | iium-35362 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:43:17Z |
| publishDate | 2014 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-353622021-01-18T05:14:41Z http://irep.iium.edu.my/35362/ Anomaly detection in vessel tracking using Support Vector Machines (SVMs) Dwi Handayani, Dini Oktarina Sediono, Wahju Shah, Asadullah TK5101 Telecommunication. Including telegraphy, radio, radar, television The paper is devoted to supervise method approach to identify the vessel anomaly behavior in waterways using the Automated Identification System (AIS) vessel reporting data. In this work, we describe the use of SVMs to detect the vessel anomaly behavior. The SVMs is a supervised method that needs some pre knowledge to extract the maritime movement patterns of AIS raw data into information. This is the basis to remodel information into a meaningful and valuable form. The result of this work shows that the SVMs technique is applicable to be used for the identification of vessel anomaly behavior. It is proved that the best accuracy result is obtained from dividing raw data into 70% for training and 30% for testing stages. 2014-12 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/35362/1/asadullah.pdf Dwi Handayani, Dini Oktarina and Sediono, Wahju and Shah, Asadullah (2014) Anomaly detection in vessel tracking using Support Vector Machines (SVMs). In: 2nd International Conference on Advanced Computer Science Applications and Technologies (ACSAT2013), 22-24 December 2013, Kuching, Sarawak, Malaysia. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6836578&tag=1 |
| spellingShingle | TK5101 Telecommunication. Including telegraphy, radio, radar, television Dwi Handayani, Dini Oktarina Sediono, Wahju Shah, Asadullah Anomaly detection in vessel tracking using Support Vector Machines (SVMs) |
| title | Anomaly detection in vessel tracking using Support Vector Machines (SVMs) |
| title_full | Anomaly detection in vessel tracking using Support Vector Machines (SVMs) |
| title_fullStr | Anomaly detection in vessel tracking using Support Vector Machines (SVMs) |
| title_full_unstemmed | Anomaly detection in vessel tracking using Support Vector Machines (SVMs) |
| title_short | Anomaly detection in vessel tracking using Support Vector Machines (SVMs) |
| title_sort | anomaly detection in vessel tracking using support vector machines (svms) |
| topic | TK5101 Telecommunication. Including telegraphy, radio, radar, television |
| url | http://irep.iium.edu.my/35362/ http://irep.iium.edu.my/35362/ http://irep.iium.edu.my/35362/1/asadullah.pdf |