IEEE CIS Outstanding Student-Paper Travel Grants Citation: 23#
Fuzzy modeling has been widely and successfully applied to solve control problems. Traditional fuzzy modeling requires either complete experts?? knowledge or large data sets to generate rule bases that can fully cover the input domain. Although fuzzy rule interpolation (FRI) relaxes this requirement by approximating rules using their neighboring ones, it is still difficult for some real world applications to obtain sufficient experts?? knowledge and data to generate a reasonable sparse rule base to support FRI. Also, the generated rule bases are usually fixed and ther
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Jie Li, Hubert P. H. Shum, Xin Fu, Graham Sexton and Longzhi Yang, "Experience-Based Rule Base Generation and Adaptation for Fuzzy Interpolation," in FUZZ-IEEE '16: Proceedings of the 2016 IEEE International Conference on Fuzzy Systems, pp. 102-109, Vancouver, Canada, IEEE, 7 2016.
Last updated on 17 September 2023