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Situation recognition using soft computing techniques
Includes bibliographical references.
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Computer Science
2015
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| _version_ | 1867613620225966080 |
|---|---|
| access_status_str | Open Access |
| author | Machaka, Pheeha |
| author2 | Bagula, Antoine |
| author_browse | Bagula, Antoine Machaka, Pheeha |
| author_facet | Bagula, Antoine Machaka, Pheeha |
| author_sort | Machaka, Pheeha |
| collection | Thesis |
| description | Includes bibliographical references. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/11225 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:39:02.580Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Department of Computer Science |
| publisherStr | Department of Computer Science |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/11225 Situation recognition using soft computing techniques Machaka, Pheeha Bagula, Antoine Computer Science Includes bibliographical references. The last decades have witnessed the emergence of a large number of devices pervasively launched into our daily lives as systems producing and collecting data from a variety of information sources to provide different services to different users via a variety of applications. These include infrastructure management, business process monitoring, crisis management and many other system-monitoring activities. Being processed in real-time, these information production/collection activities raise an interest for live performance monitoring, analysis and reporting, and call for data-mining methods in the recognition, prediction, reasoning and controlling of the performance of these systems by controlling changes in the system and/or deviations from normal operation. In recent years, soft computing methods and algorithms have been applied to data mining to identify patterns and provide new insight into data. This thesis revisits the issue of situation recognition for systems producing massive datasets by assessing the relevance of using soft computing techniques for finding hidden pattern in these systems. 2015-01-03T18:31:30Z 2015-01-03T18:31:30Z 2012 Master Thesis Masters MSc http://hdl.handle.net/11427/11225 eng application/pdf Department of Computer Science Faculty of Science University of Cape Town |
| spellingShingle | Computer Science Machaka, Pheeha Situation recognition using soft computing techniques |
| thesis_degree_str | Master's |
| title | Situation recognition using soft computing techniques |
| title_full | Situation recognition using soft computing techniques |
| title_fullStr | Situation recognition using soft computing techniques |
| title_full_unstemmed | Situation recognition using soft computing techniques |
| title_short | Situation recognition using soft computing techniques |
| title_sort | situation recognition using soft computing techniques |
| topic | Computer Science |
| url | http://hdl.handle.net/11427/11225 |
| work_keys_str_mv | AT machakapheeha situationrecognitionusingsoftcomputingtechniques |