Abstract
In this paper, rough set theory is used to extract roughly-correct inference rules from information systems. Based on this idea, the learning algorithm ERCR is presented. In order to refine the learned roughly-correct inference rules, the knowledge-based neural network is used. The method presented here sufficiently combines the advantages of rough set theory and neural network.
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References
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Wang Shitong is a Professor and the head of the Department of Computer at East China Shipbuilding Institute. Up to now, he has published 5 books and 92 papers in international/national journals or in international conferences. His research interests include artificial intelligence, neural networks, fuzzy system and rough set theory.
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Shitong, W., Scott, E. & Gamermann, A. Extract rules by using rough set and knowledge-based NN. J. of Comput. Sci. & Technol. 13, 279–284 (1998). https://doi.org/10.1007/BF02943196
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DOI: https://doi.org/10.1007/BF02943196