{"created":"2023-05-15T14:56:17.991226+00:00","id":76466,"links":{},"metadata":{"_buckets":{"deposit":"49cc2a9c-d298-423f-99ec-76ec719fba13"},"_deposit":{"created_by":1,"id":"76466","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"76466"},"status":"published"},"_oai":{"id":"oai:repo.qst.go.jp:00076466","sets":["10:29"]},"author_link":["775086","775087","775088","775089"],"item_10005_date_7":{"attribute_name":"発表年月日","attribute_value_mlt":[{"subitem_date_issued_datetime":"2019-08-08","subitem_date_issued_type":"Issued"}]},"item_10005_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"乱流流束の分布勾配に対する敏感な依存性のために、硬い輸送モデルを用いた安定した分布予測は困難である。この困難を克服するため、大域的最適化手法を用いた新しい定常輸送コードGOTRESSが開発された。硬い輸送モデルを用いたシミュレーションで生じがちな数値的不安定なしに、滑らかな拡散係数や温度分布を得ることが出来る。輸送モデルを模擬するニューラルネットワークモデルを開発することにより、計算時間が掛かりがちな大域的最適化手法の弱点を克服して高速な計算を実現した。ハイパーパラメータ最適化により、モデルの精度を向上させた。","subitem_description_type":"Abstract"}]},"item_10005_description_6":{"attribute_name":"会議概要（会議名, 開催地, 会期, 主催者等）","attribute_value_mlt":[{"subitem_description":"第25回NEXT（数値トカマク）研究会","subitem_description_type":"Other"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"本多, 充"}],"nameIdentifiers":[{"nameIdentifier":"775086","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"成田, 絵美"}],"nameIdentifiers":[{"nameIdentifier":"775087","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Honda, Mitsuru","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"775088","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Narita, Emi","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"775089","nameIdentifierScheme":"WEKO"}]}]},"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":"conference object","resourceuri":"http://purl.org/coar/resource_type/c_c94f"}]},"item_title":"Machine-learning assisted steady-state profile predictions using global optimization techniques","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Machine-learning assisted steady-state profile predictions using global optimization techniques"}]},"item_type_id":"10005","owner":"1","path":["29"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-08-13"},"publish_date":"2019-08-13","publish_status":"0","recid":"76466","relation_version_is_last":true,"title":["Machine-learning assisted steady-state profile predictions using global optimization techniques"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-05-16T00:23:07.774674+00:00"}