Temporal trends analysis for dengue outbreak and network threats severity prediction accuracy improvement
Time series analysis is one of the major techniques in capturing trends and pattern of the occurrence for future forecasting. Existing but scarce work have developed temporal-based techniques which target to either predict movement (increase or decrease) or quantify the possibility of the predicted...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Digital Information Research Foundation
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/82150/ http://psasir.upm.edu.my/id/eprint/82150/1/Temporal%20trends%20analysis%20.pdf |
| _version_ | 1848859246909718528 |
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| author | Mohd Sharef, Nurfadhlina Husin, Nor Azura Kasmiran, Khairul Azhar Ninggal, Mohd Izuan |
| author_facet | Mohd Sharef, Nurfadhlina Husin, Nor Azura Kasmiran, Khairul Azhar Ninggal, Mohd Izuan |
| author_sort | Mohd Sharef, Nurfadhlina |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Time series analysis is one of the major techniques in capturing trends and pattern of the occurrence for future forecasting. Existing but scarce work have developed temporal-based techniques which target to either predict movement (increase or decrease) or quantify the possibility of the predicted event to happen. Man of these techniques focus on the values of the time series attribute but there is no available work on dengue or intrusion logs that focus on temporal trend analysis based on temporal relations mining. In this work the proposed technique utilize the temporal trends analysis of the observational attributes towards the pattern of the target’s attribute values. In this work, we propose a new temporal trends analysis approach that uses temporal relation mining in forecasting dengue outbreak and cyber intrusion.We leverage the temporal abstractions and temporal logic to define patterns with the goal to optimize prediction accuracy. From the experiment conducted, the results showed that the proposed approach has better prediction as compared to the baseline. |
| first_indexed | 2025-11-15T12:26:18Z |
| format | Article |
| id | upm-82150 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:26:18Z |
| publishDate | 2019 |
| publisher | Digital Information Research Foundation |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-821502021-02-01T19:59:00Z http://psasir.upm.edu.my/id/eprint/82150/ Temporal trends analysis for dengue outbreak and network threats severity prediction accuracy improvement Mohd Sharef, Nurfadhlina Husin, Nor Azura Kasmiran, Khairul Azhar Ninggal, Mohd Izuan Time series analysis is one of the major techniques in capturing trends and pattern of the occurrence for future forecasting. Existing but scarce work have developed temporal-based techniques which target to either predict movement (increase or decrease) or quantify the possibility of the predicted event to happen. Man of these techniques focus on the values of the time series attribute but there is no available work on dengue or intrusion logs that focus on temporal trend analysis based on temporal relations mining. In this work the proposed technique utilize the temporal trends analysis of the observational attributes towards the pattern of the target’s attribute values. In this work, we propose a new temporal trends analysis approach that uses temporal relation mining in forecasting dengue outbreak and cyber intrusion.We leverage the temporal abstractions and temporal logic to define patterns with the goal to optimize prediction accuracy. From the experiment conducted, the results showed that the proposed approach has better prediction as compared to the baseline. Digital Information Research Foundation 2019-06 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/82150/1/Temporal%20trends%20analysis%20.pdf Mohd Sharef, Nurfadhlina and Husin, Nor Azura and Kasmiran, Khairul Azhar and Ninggal, Mohd Izuan (2019) Temporal trends analysis for dengue outbreak and network threats severity prediction accuracy improvement. Journal of Digital Information Management, 17 (3). pp. 122-132. ISSN 0972-7272 10.6025/jdim/2019/17/3/122-132 |
| spellingShingle | Mohd Sharef, Nurfadhlina Husin, Nor Azura Kasmiran, Khairul Azhar Ninggal, Mohd Izuan Temporal trends analysis for dengue outbreak and network threats severity prediction accuracy improvement |
| title | Temporal trends analysis for dengue outbreak and network threats severity prediction accuracy improvement |
| title_full | Temporal trends analysis for dengue outbreak and network threats severity prediction accuracy improvement |
| title_fullStr | Temporal trends analysis for dengue outbreak and network threats severity prediction accuracy improvement |
| title_full_unstemmed | Temporal trends analysis for dengue outbreak and network threats severity prediction accuracy improvement |
| title_short | Temporal trends analysis for dengue outbreak and network threats severity prediction accuracy improvement |
| title_sort | temporal trends analysis for dengue outbreak and network threats severity prediction accuracy improvement |
| url | http://psasir.upm.edu.my/id/eprint/82150/ http://psasir.upm.edu.my/id/eprint/82150/ http://psasir.upm.edu.my/id/eprint/82150/1/Temporal%20trends%20analysis%20.pdf |