A new approach to generate weighted fuzzy rules using genetic algorithms for estimating null values |
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| Authors: | Shyi-Ming Chen Chung-Ming Huang |
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| Affiliation: | aDepartment of Computer Science and Information Engineering, National Taiwan University of Science and Technology, 43, Section 4, Keelung Road, Taipei 106, Taiwan, ROC;bDepartment of Electronic Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC;cDepartment of Computer Science and Information Engineering, Jinwen University of Science and Technology, Taipei County, Taiwan, ROC |
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| Abstract: | In this paper, we present a new method to generate weighted fuzzy rules using genetic algorithms for estimating null values in relational database systems, where there are negative functional dependency relationships between attributes. The proposed method can get higher average estimated accuracy rates than the method presented in Chen, S. M., & Huang, C. M. (2003). Generating weighted fuzzy rules from relational database systems for estimating null values using genetic algorithms. IEEE Transactions on Fuzzy Systems, 11(4), 495–506]. |
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| Keywords: | Fuzzy rules Genetic algorithms Membership functions Negative dependency relationship Null values Relational database systems |
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