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Such nonlinear mapping cannot be provided by conventional methods for sparse fuzzy rules. In evaluating the proposed method, mean square errors are adopted to indicate difference between deduced consequences and fuzzy sets transformed by nonlinear fuzzy-valued functions to be represented with sparse fuzzy rules. Simulation results show that the proposed method can follow the nonlinear fuzzy-valued functions. The proposed method contributes to both reducing the number of fuzzy rules and providing nonlinear mapping with sparse rule bases.<\/jats:p>","DOI":"10.20965\/jaciii.2011.p0264","type":"journal-article","created":{"date-parts":[[2016,4,14]],"date-time":"2016-04-14T06:08:34Z","timestamp":1460614114000},"page":"264-287","source":"Crossref","is-referenced-by-count":11,"title":["Inference for Nonlinear Mapping with Sparse Fuzzy Rules Based on Multi-Level Interpolation"],"prefix":"10.20965","volume":"15","author":[{"given":"Kiyohiko","family":"Uehara","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"Ibaraki University, Hitachi 316-8511, Japan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shun","family":"Sato","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaoru","family":"Hirota","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"Tokyo Institute of Technology, Yokohama 226-8502, Japan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"8550","published-online":{"date-parts":[[2011,5,20]]},"reference":[{"key":"key-10.20965\/jaciii.2011.p0264-1","doi-asserted-by":"crossref","unstructured":"I. 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