Generation of explicit knowledge from temporal data
Expert decisions are usually based on experience knowledge regarding the decision environments. However due to the mobility or high turn-over of expert whether due to promotion, resignation or other reasons, there is a need to capture expert knowledge especially those involved critical decision.This...
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my.uum.repo.34022015-05-12T02:48:34Z http://repo.uum.edu.my/3402/ Generation of explicit knowledge from temporal data Md. Norwawi, Norita Ku-Mahamud, Ku Ruhana Deris, Safaai QA76 Computer software Expert decisions are usually based on experience knowledge regarding the decision environments. However due to the mobility or high turn-over of expert whether due to promotion, resignation or other reasons, there is a need to capture expert knowledge especially those involved critical decision.This paper will describe an approach of capturing expert knowledge through past operation data. An explicit knowledge extraction technique from temporal data representing reservoir operation will be presented.Rules regarding decision on the number of spillway gates to be open to release excess water from the dam will be discovered from the historical data. Temporal information related to a decision will be captured through sliding window method and classified into unique decision classes. This information can be transformed into decision rules for easy interpretation and understanding. These rules can be hrther use to guide future operation decisions. 2004 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/3402/1/Ku.pdf Md. Norwawi, Norita and Ku-Mahamud, Ku Ruhana and Deris, Safaai (2004) Generation of explicit knowledge from temporal data. In: Knowledge Management International Conference and Exhibition 2004 (KMICE 2004) , 14-15 February 2004, Evergreen Laurel Hotel, Penang . http://www.kmice.cms.net.my |
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QA76 Computer software Md. Norwawi, Norita Ku-Mahamud, Ku Ruhana Deris, Safaai Generation of explicit knowledge from temporal data |
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Expert decisions are usually based on experience knowledge regarding the decision environments. However due to the mobility or high turn-over of expert whether due to promotion, resignation or other reasons, there is a need to capture expert knowledge especially those involved critical decision.This paper will describe an approach of capturing expert knowledge through past operation data. An explicit knowledge extraction technique from temporal data representing reservoir operation will be presented.Rules regarding decision on the number of spillway gates to be open to release excess water from the dam will be discovered from the historical data. Temporal information related to a decision will be captured through sliding window method and classified into unique decision classes. This information can be transformed into decision rules for easy interpretation and understanding. These rules can be hrther use to guide future operation decisions. |
format |
Conference or Workshop Item |
author |
Md. Norwawi, Norita Ku-Mahamud, Ku Ruhana Deris, Safaai |
author_facet |
Md. Norwawi, Norita Ku-Mahamud, Ku Ruhana Deris, Safaai |
author_sort |
Md. Norwawi, Norita |
title |
Generation of explicit knowledge from temporal data |
title_short |
Generation of explicit knowledge from temporal data |
title_full |
Generation of explicit knowledge from temporal data |
title_fullStr |
Generation of explicit knowledge from temporal data |
title_full_unstemmed |
Generation of explicit knowledge from temporal data |
title_sort |
generation of explicit knowledge from temporal data |
publishDate |
2004 |
url |
http://repo.uum.edu.my/3402/1/Ku.pdf http://repo.uum.edu.my/3402/ http://www.kmice.cms.net.my |
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1644278494858838016 |
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13.149126 |