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A genetic algorithm methodology for data mining and intelligent knowledge acquisition
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DOI：10.1016/S0360-8352(01)00036-5.png)
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Abstract
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Data mining is a process that uses available technology to bridge the gap between data and logical decision making. The terminology itself provides a promising view of a systematic data manipulation for extracting useful information and knowledge from the high volume of data. Numerous techniques are developed to fulfill this goal. Implement data mining in an organization would impact every aspect and requires both hardware and software development. This paper outlines a series of discussions and description for data mining and its methodology. First, the definition of data mining along with the purposes and growing needs for such a technology is presented. A six-step methodology for data mining is then presented. Finally, steps from the methodology are applied in a case study to develop a GA-Based system for intelligent knowledge discovery for machine diagnosis. (C) 2001 Elsevier Science Ltd. All rights reserved.
Keywords:
intelligent diagonis system
genetic algorithm
design of experiment
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