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- W2022005257 abstract "Rough set theory is a powerful tool in deal with vagueness and uncertainty. It is particularly suitable to discover hidden and potentially useful knowledge in data and can be used to reduce features and extract rules. This paper introduces the basic concepts and fundamental elements of the rough set theory. A reduction algorithm that integrates a priori with significance is proposed to illustrate how the rough set theory could be used to extract fault features of the condenser in a power plant. Two testing examples are then presented to demonstrate the effectiveness of the theory in fault diagnosis." @default.
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- W2022005257 date "2003-01-01" @default.
- W2022005257 modified "2023-09-27" @default.
- W2022005257 title "Application of Rough Set Theory to Data Mining of Condenser Diagnosis in Power Plants" @default.
- W2022005257 doi "https://doi.org/10.1115/ijpgc2003-40135" @default.
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