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A learning multiple-valued logic networkusing genetic algorithm
http://hdl.handle.net/2297/36317
http://hdl.handle.net/2297/363173379472d-5ebf-444a-8a2f-ceb2c2cc171e
名前 / ファイル | ライセンス | アクション |
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2017-10-03 | |||||
タイトル | ||||||
タイトル | A learning multiple-valued logic networkusing genetic algorithm | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
Todo, Yuki
× Todo, Yuki× Mitsui, Takahiro |
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書誌情報 |
International Journal of Innovative Computing, Information and Control 巻 10, 号 2, p. 565-574, 発行日 2014-04-01 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1349-4198 | |||||
NCID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA12218449 | |||||
出版者 | ||||||
出版者 | ICIC International / Inderscience | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | This paper describes a genetic algorithm based learning Multiple-Value Logic (MVL) network. The proposed learning network operates on a population of candidate window parameters to produce new window parameters with lower errors between the desired outputs and the actual outputs of the MVL network. Thus, the learning MVL network has a large number of search points, making it possible to obtain a global min- imum. The learning capability of the proposed MVL network with genetic algorithm is con rmed by simulations on several typical MVL functions. The simulation results show that the genetic algorithm based learning MVL network efficiently nds the appropriate network, window parameters, and bias, so that the MVL functions, especially for those relatively small problems. | |||||
著者版フラグ | ||||||
出版タイプ | AM | |||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa |