Forest fire pattern extraction and rule generation using sliding window technique
The sliding window technique is being used to extract patterns of forest fire which consists of burnt area size, temperature, relative humidity, wind speed and rainfall.The initial data is being transformed by changing the continuous values of the attributes into categorical value. Extracted pattern...
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my.uum.repo.135372015-04-02T02:54:31Z http://repo.uum.edu.my/13537/ Forest fire pattern extraction and rule generation using sliding window technique Ku-Mahamud, Ku Ruhana Khor, Jia Yun QA76 Computer software The sliding window technique is being used to extract patterns of forest fire which consists of burnt area size, temperature, relative humidity, wind speed and rainfall.The initial data is being transformed by changing the continuous values of the attributes into categorical value. Extracted patterns are then being grouped based on the size of burnt are.Rules are then generated by transforming the categorical values into intervals and the merging different records into the same rules.The rule generation stage produces eight distinct patterns of meteorological conditions that could predict the size of forest fire. 2009-06-24 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/13537/1/PID224.pdf Ku-Mahamud, Ku Ruhana and Khor, Jia Yun (2009) Forest fire pattern extraction and rule generation using sliding window technique. In: International Conference on Computing and Informatics 2009 (ICOCI09), 24-25 June 2009, Legend Hotel, Kuala Lumpur. http://www.icoci.cms.net.my |
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QA76 Computer software Ku-Mahamud, Ku Ruhana Khor, Jia Yun Forest fire pattern extraction and rule generation using sliding window technique |
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The sliding window technique is being used to extract patterns of forest fire which consists of burnt area size, temperature, relative humidity, wind speed and rainfall.The initial data is being transformed by changing the continuous values of the attributes into categorical value. Extracted patterns are then being grouped based on the size of burnt are.Rules are then generated by transforming the categorical values into
intervals and the merging different records into the same rules.The rule generation stage produces eight distinct patterns of meteorological conditions that could predict the size of forest fire. |
format |
Conference or Workshop Item |
author |
Ku-Mahamud, Ku Ruhana Khor, Jia Yun |
author_facet |
Ku-Mahamud, Ku Ruhana Khor, Jia Yun |
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Ku-Mahamud, Ku Ruhana |
title |
Forest fire pattern extraction and rule generation using sliding window technique |
title_short |
Forest fire pattern extraction and rule generation using sliding window technique |
title_full |
Forest fire pattern extraction and rule generation using sliding window technique |
title_fullStr |
Forest fire pattern extraction and rule generation using sliding window technique |
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Forest fire pattern extraction and rule generation using sliding window technique |
title_sort |
forest fire pattern extraction and rule generation using sliding window technique |
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2009 |
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http://repo.uum.edu.my/13537/1/PID224.pdf http://repo.uum.edu.my/13537/ http://www.icoci.cms.net.my |
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1644281212444868608 |
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13.211869 |