Download | - View accepted manuscript: Use of Decision-Tree Induction for Process Optimization and Knowledge Refinement of an Industrial Process (PDF, 631 KiB)
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Author | Search for: Famili, Fazel |
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Format | Text, Article |
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Subject | decision-tree induction; process optimization; optimisation du processus |
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Abstract | Development of expert systems involves knowledge acquisition which can be supported by applying machine learning techniques. This paper presents the basic idea of using decision-tree induction in process optimization and development of the domain model of electrochemical machining (ECM). It further discusses how decision-tree induction is used to build and refine the knowledge base of the process. The idea of developing an intelligent supervisory system with a learning component (IMAFO, Intelligent MAnufacturing FOreman) that is already implemented is briefly introduced. The results of applying IMAFO for analyzing data form the ECM process are presented. How the domain model of the process (electrochemical machining) is built from the initial known information and how the results of decision-tree induction can be used to optimize the model of the process and further refine the knowledge base are shown. Two examples are given to demonstrate how new rules (to be included in the knowledge base of an expert system) are generated from the rules induced by IMAFO. The procedure to refine these types of rules is also explained. |
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Publication date | 1994 |
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In | |
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Language | English |
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NRC number | NRCC 35070 |
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NPARC number | 9145781 |
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Export citation | Export as RIS |
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Report a correction | Report a correction (opens in a new tab) |
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Record identifier | 2a3ba591-edfe-4d5c-ace9-bc4e67c5441d |
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Record created | 2009-06-25 |
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Record modified | 2020-04-27 |
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