{"_buckets": {"deposit": "07ddf614-cf14-4abd-b797-5450c0271280"}, "_deposit": {"created_by": 3, "id": "8393", "owners": [3], "pid": {"revision_id": 0, "type": "depid", "value": "8393"}, "status": "published"}, "_oai": {"id": "oai:kanazawa-u.repo.nii.ac.jp:00008393", "sets": ["936"]}, "author_link": ["11731", "11748"], "item_4_biblio_info_8": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2014-04-01", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "2", "bibliographicPageEnd": "574", "bibliographicPageStart": "565", "bibliographicVolumeNumber": "10", "bibliographic_titles": [{"bibliographic_title": "International Journal of Innovative Computing, Information and Control"}]}]}, "item_4_description_21": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "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.", "subitem_description_type": "Abstract"}]}, "item_4_publisher_17": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "ICIC International / Inderscience"}]}, "item_4_source_id_11": {"attribute_name": "NCID", "attribute_value_mlt": [{"subitem_source_identifier": "AA12218449", "subitem_source_identifier_type": "NCID"}]}, "item_4_source_id_9": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "1349-4198", "subitem_source_identifier_type": "ISSN"}]}, "item_4_version_type_25": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_ab4af688f83e57aa", "subitem_version_type": "AM"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Todo, Yuki"}], "nameIdentifiers": [{"nameIdentifier": "11731", "nameIdentifierScheme": "WEKO"}, {"nameIdentifier": "70636927", "nameIdentifierScheme": "金沢大学研究者情報", "nameIdentifierURI": "http://ridb.kanazawa-u.ac.jp/public/detail.php?kaken=70636927"}, {"nameIdentifier": "70636927", "nameIdentifierScheme": "研究者番号", "nameIdentifierURI": "https://nrid.nii.ac.jp/nrid/1000070636927"}]}, {"creatorNames": [{"creatorName": "Mitsui, Takahiro"}], "nameIdentifiers": [{"nameIdentifier": "11748", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2017-10-03"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "TE-PR-TODO-Y-565.pdf", "filesize": [{"value": "545.2 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 545200.0, "url": {"label": "TE-PR-TODO-Y-565.pdf", "url": "https://kanazawa-u.repo.nii.ac.jp/record/8393/files/TE-PR-TODO-Y-565.pdf"}, "version_id": "7b994ce9-65b2-4c6a-8936-d18d2d8efedf"}]}, "item_keyword": {"attribute_name": "キーワード", "attribute_value_mlt": [{"subitem_subject": "Multiple-valued logic", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Genetic algorithm", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Learning", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Global minimum", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Local minimum", "subitem_subject_scheme": "Other"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "A learning multiple-valued logic networkusing genetic algorithm", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "A learning multiple-valued logic networkusing genetic algorithm"}]}, "item_type_id": "4", "owner": "3", "path": ["936"], "permalink_uri": "http://hdl.handle.net/2297/36317", "pubdate": {"attribute_name": "公開日", "attribute_value": "2017-10-03"}, "publish_date": "2017-10-03", "publish_status": "0", "recid": "8393", "relation": {}, "relation_version_is_last": true, "title": ["A learning multiple-valued logic networkusing genetic algorithm"], "weko_shared_id": 3}