{"created":"2023-06-19T09:50:57.886195+00:00","id":7922,"links":{},"metadata":{"_buckets":{"deposit":"ecc09936-ada4-4811-813d-5790b6308183"},"_deposit":{"created_by":3,"id":"7922","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"7922"},"status":"published"},"_oai":{"id":"oai:fukuyama-u.repo.nii.ac.jp:00007922","sets":["502:505:675:695:696"]},"author_link":["42585","42582","42592","42584","42591","42594","42586","42588","42593","42580","42583","42590","42587","42581","42589"],"item_1_biblio_info_14":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1994-09","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicPageEnd":"38","bibliographicPageStart":"31","bibliographicVolumeNumber":"18","bibliographic_titles":[{"bibliographic_title":"福山大学工学部紀要"}]}]},"item_1_creator_6":{"attribute_name":"著者名(日)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"田中, 始男"}],"nameIdentifiers":[{"nameIdentifier":"42580","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"坪井, 始"}],"nameIdentifiers":[{"nameIdentifier":"42581","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"小林, 富士男"}],"nameIdentifiers":[{"nameIdentifier":"42582","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"美咲, 隆吉"}],"nameIdentifiers":[{"nameIdentifier":"42583","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"高橋, 政行"}],"nameIdentifiers":[{"nameIdentifier":"42584","nameIdentifierScheme":"WEKO"}]}]},"item_1_description_1":{"attribute_name":"ページ属性","attribute_value_mlt":[{"subitem_description":"P(論文)","subitem_description_type":"Other"}]},"item_1_description_12":{"attribute_name":"抄録(英)","attribute_value_mlt":[{"subitem_description":"Distribution patterns of grand wire current along transmission lines have been analyzed by a experts in order to find the fault location. Various types of fault location methods using multi-layered feed forward type neural network models have been proposed and these efficiencies have been shown in several papers. The amplitudes and the phase angles are used as the input data of the neural network. If we use complex number for the neural network, we can relate the amplitude and the phase angle to each other. In this paper, we propose a fault location method using the multi-layered feed forward type neural network model. In the proposed method, the neurons are expressed by the sigmoid functions which are extend to the complex number and we use the complex back propagation learning algorithm.","subitem_description_type":"Other"}]},"item_1_full_name_7":{"attribute_name":"著者名よみ","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"42585","nameIdentifierScheme":"WEKO"}],"names":[{"name":"タナカ, モトオ"}]},{"nameIdentifiers":[{"nameIdentifier":"42586","nameIdentifierScheme":"WEKO"}],"names":[{"name":"ツボイ, ハジメ"}]},{"nameIdentifiers":[{"nameIdentifier":"42587","nameIdentifierScheme":"WEKO"}],"names":[{"name":"コバヤシ, フジオ"}]},{"nameIdentifiers":[{"nameIdentifier":"42588","nameIdentifierScheme":"WEKO"}],"names":[{"name":"ミサキ, タカヨシ"}]},{"nameIdentifiers":[{"nameIdentifier":"42589","nameIdentifierScheme":"WEKO"}],"names":[{"name":"タカハシ, マサユキ"}]}]},"item_1_full_name_8":{"attribute_name":"著者名(英)","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"42590","nameIdentifierScheme":"WEKO"}],"names":[{"name":"TNAKA, Motoo","nameLang":"en"}]},{"nameIdentifiers":[{"nameIdentifier":"42591","nameIdentifierScheme":"WEKO"}],"names":[{"name":"TSUBOI, Hajime","nameLang":"en"}]},{"nameIdentifiers":[{"nameIdentifier":"42592","nameIdentifierScheme":"WEKO"}],"names":[{"name":"KOBAYASHI, Fujio","nameLang":"en"}]},{"nameIdentifiers":[{"nameIdentifier":"42593","nameIdentifierScheme":"WEKO"}],"names":[{"name":"MISAKI, Takayoshi","nameLang":"en"}]},{"nameIdentifiers":[{"nameIdentifier":"42594","nameIdentifierScheme":"WEKO"}],"names":[{"name":"TAKAHASHI, Masayuki","nameLang":"en"}]}]},"item_1_source_id_13":{"attribute_name":"雑誌書誌ID","attribute_value_mlt":[{"subitem_source_identifier":"AN00217655","subitem_source_identifier_type":"NCID"}]},"item_1_text_9":{"attribute_name":"著者所属(日)","attribute_value_mlt":[{"subitem_text_value":"福山大学工学部情報処理工学科"},{"subitem_text_value":"福山大学工学部情報処理工学科"},{"subitem_text_value":"福山大学工学部情報処理工学科"},{"subitem_text_value":"福山大学工学部情報処理工学科"},{"subitem_text_value":"福山大学工学部情報処理工学科"}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"1994-09-01"}],"displaytype":"detail","filename":"KJ00005781310.pdf","filesize":[{"value":"525.6 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://fukuyama-u.repo.nii.ac.jp/record/7922/files/KJ00005781310.pdf"},"version_id":"e10e56f0-af86-4974-87d6-83aeadf15f15"}]},"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":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"複素数を用いたニューラルネットワークによる送電線の故障区間標定","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"複素数を用いたニューラルネットワークによる送電線の故障区間標定"},{"subitem_title":"Estimation of Fault Location for Transmission Lines by Neural Network Using Complex Back Propagation Learning Algorithm","subitem_title_language":"en"}]},"item_type_id":"1","owner":"3","path":["696"],"pubdate":{"attribute_name":"公開日","attribute_value":"1994-09-01"},"publish_date":"1994-09-01","publish_status":"0","recid":"7922","relation_version_is_last":true,"title":["複素数を用いたニューラルネットワークによる送電線の故障区間標定"],"weko_creator_id":"3","weko_shared_id":-1},"updated":"2023-06-19T10:33:47.346150+00:00"}