{"created":"2023-05-15T11:55:13.309494+00:00","id":52,"links":{},"metadata":{"_buckets":{"deposit":"1a4879be-9e1b-4b96-99ee-ac18eb44c6c5"},"_deposit":{"created_by":3,"id":"52","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"52"},"status":"published"},"_oai":{"id":"oai:kyutech.repo.nii.ac.jp:00000052","sets":["8:9"]},"author_link":["207","208","209","210","211","212"],"control_number":"52","item_21_alternative_title_18":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"Fuzzy Modeling Using a Heuristic Method and Its Application to the Prediction Diagnosis of Ectopic Pregnancy","subitem_alternative_title_language":"en"}]},"item_21_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1996-08-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicPageEnd":"112","bibliographicPageStart":"103","bibliographicVolumeNumber":"2","bibliographic_titles":[{"bibliographic_title":"Biomedical fuzzy and human sciences : the official journal of the Biomedical Fuzzy Systems Association"}]}]},"item_21_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"本論文では, ヒューリスティック・クラスタリングにより入力変数空間をファジィ分割し, ファジィモデルを自動生成する手法を提案する.ヒューリスティック・クラスタリングにより人間の経験的・直観的な判断方法を利用したヒューリスティックな手法で入力変数空間をクラスタリングし, 後件部を実数値としたファジィモデルを自動生成するものである.入力変数空間を直方体状に小さく切り分け, その部分の入出力関係を線形であるとみなし, 単位法線ベクトルを計算し, 単位法線ベクトルの似ている部分を集めてクラスタとすることでファジィ分割を実現する.また, ファジィルールの後件部実数値の学習には最急降下法を用いる.提案手法の検証のために従来手法との関数の近似能力の比較結果を示し, 更に応用例として, 不妊症患者の妊娠転帰後の予後予測診断モデル, つまり, 子宮外妊娠の予測診断モデルの構築について示す. / In this paper, we propose the heuristic clustering for a fuzzy modeling. This approach devide an input variable space into some clusters by using an approach following human's experience and intuition. As input variable space is devided into a lot of subspaces, and we suppose that their relations of input variables and output variables are linear. If unit normal vectors of some subspaces are similar, their are unified as a cluster. Then, some clusters are generated. After the heuristic clustering, we set membership functions of premise parts, and values of consequent parts are learned by a steepest decent method. To verify this approach, we show nonlinear function's approximation as a result. Furthermore, as an example of application, we show fuzzy model for the predicting diagnosis of ectopic pregnancy after the pregnancy effect for infertile patients.","subitem_description_type":"Abstract"}]},"item_21_description_60":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"subitem_description":"Journal Article","subitem_description_type":"Other"}]},"item_21_full_name_3":{"attribute_name":"著者別名","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"210","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Maeda, Mikio","nameLang":"en"}]},{"nameIdentifiers":[{"nameIdentifier":"211","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Hayashida, Katsuhiko","nameLang":"en"}]},{"nameIdentifiers":[{"nameIdentifier":"212","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Murakami, Shuta","nameLang":"en"}]}]},"item_21_publisher_7":{"attribute_name":"出版社","attribute_value_mlt":[{"subitem_publisher":"バイオメディカル・ファジィ・システム学会"}]},"item_21_relation_66":{"attribute_name":"NAID","attribute_value_mlt":[{"subitem_relation_type":"isIdenticalTo","subitem_relation_type_id":{"subitem_relation_type_id_text":"110003930455","subitem_relation_type_select":"NAID"}}]},"item_21_rights_13":{"attribute_name":"著作権関連情報","attribute_value_mlt":[{"subitem_rights":"バイオメディカル・ファジィ・システム学会. 本文データは学協会の許諾に基づきCiNiiから複製したものである"}]},"item_21_select_59":{"attribute_name":"査読の有無","attribute_value_mlt":[{"subitem_select_item":"yes"}]},"item_21_source_id_8":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2185-2421","subitem_source_identifier_type":"PISSN"}]},"item_21_text_36":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"九州工業大学工学部"},{"subitem_text_value":"九州工業大学工学部"},{"subitem_text_value":"九州工業大学工学部"},{"subitem_text_value":"Department of Computer Engineering, Faculty of Engineering, Kyushu Institute of Technology"},{"subitem_text_value":"Department of Computer Engineering, Faculty of Engineering, Kyushu Institute of Technology"},{"subitem_text_value":"Department of Computer Engineering, Faculty of Engineering, Kyushu Institute of Technology"}]},"item_21_version_type_58":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"前田, 幹夫","creatorNameLang":"ja"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"林田, 克彦","creatorNameLang":"ja"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"村上, 周太","creatorNameLang":"ja"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2007-11-13"}],"displaytype":"detail","filename":"2185-2421_2-1-p103.pdf","filesize":[{"value":"1.1 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"2185-2421_2-1-p103.pdf","url":"https://kyutech.repo.nii.ac.jp/record/52/files/2185-2421_2-1-p103.pdf"},"version_id":"f0613f45-540f-49b8-825c-192f03e7a7db"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ファジィモデリング","subitem_subject_scheme":"Other"},{"subitem_subject":"ファジィエキスパートシステム","subitem_subject_scheme":"Other"},{"subitem_subject":"簡略ファジィ推論","subitem_subject_scheme":"Other"},{"subitem_subject":"クラスタリング","subitem_subject_scheme":"Other"},{"subitem_subject":"診断","subitem_subject_scheme":"Other"},{"subitem_subject":"子宮外妊娠","subitem_subject_scheme":"Other"},{"subitem_subject":"fuzzy modeling","subitem_subject_scheme":"Other"},{"subitem_subject":"fuzzy expert system","subitem_subject_scheme":"Other"},{"subitem_subject":"simplified fuzzy reasoning","subitem_subject_scheme":"Other"},{"subitem_subject":"clustering","subitem_subject_scheme":"Other"},{"subitem_subject":"diagnosis","subitem_subject_scheme":"Other"},{"subitem_subject":"ectopic pregnancy","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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":"ヒューリスティックな手法を用いたファジィモデリングとその予測診断への応用","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ヒューリスティックな手法を用いたファジィモデリングとその予測診断への応用","subitem_title_language":"ja"}]},"item_type_id":"21","owner":"3","path":["9"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2007-11-13"},"publish_date":"2007-11-13","publish_status":"0","recid":"52","relation_version_is_last":true,"title":["ヒューリスティックな手法を用いたファジィモデリングとその予測診断への応用"],"weko_creator_id":"3","weko_shared_id":-1},"updated":"2024-04-02T08:43:26.309376+00:00"}