{"created":"2023-05-15T14:55:45.792945+00:00","id":75715,"links":{},"metadata":{"_buckets":{"deposit":"7ce7a810-ed49-41d5-ad20-4c18b8c88df9"},"_deposit":{"created_by":1,"id":"75715","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"75715"},"status":"published"},"_oai":{"id":"oai:repo.qst.go.jp:00075715","sets":["10:29"]},"author_link":["751737","751736","751732","751730","751733","751735","751734","751731"],"item_10005_date_7":{"attribute_name":"発表年月日","attribute_value_mlt":[{"subitem_date_issued_datetime":"2019-04-11","subitem_date_issued_type":"Issued"}]},"item_10005_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"強化学習の手法を用いてプラズマ温度分布制御を行うためのフィードバックゲインを動的に最適化するシステムを開発した。核融合プラズマの閉じ込め特性は輸送障壁の形成を通じて加熱入力に強い非線形性を示すことがあり、固定したフィードバックゲインでは十分な制御性能が得られない場合がある。本研究で開発したシステムは、各制御時刻の加熱入力と温度分布の応答の情報を入力データとして与えると次時刻の最適なフィードバックゲインを出力するように、シミュレーションでの試行錯誤から学習した。JT-60Uの実験データに対して本システムを適用し、その制御特性を検証することで、強化学習を用いたプラズマ温度分布制御システムの実験への適用可能性を評価した。","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":"22nd ITPA IOS-TG Meeting","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":"若月, 琢馬"}],"nameIdentifiers":[{"nameIdentifier":"751730","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"鈴木, 隆博"}],"nameIdentifiers":[{"nameIdentifier":"751731","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"大山, 直幸"}],"nameIdentifiers":[{"nameIdentifier":"751732","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"林, 伸彦"}],"nameIdentifiers":[{"nameIdentifier":"751733","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Wakatsuki, Takuma","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"751734","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Suzuki, Takahiro","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"751735","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Oyama, Naoyuki","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"751736","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Hayashi, Nobuhiko","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"751737","nameIdentifierScheme":"WEKO"}]}]},"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":"conference object","resourceuri":"http://purl.org/coar/resource_type/c_c94f"}]},"item_title":"Ion temperature profile control system using reinforcement learning technique","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Ion temperature profile control system using reinforcement learning technique"}]},"item_type_id":"10005","owner":"1","path":["29"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-04-25"},"publish_date":"2019-04-25","publish_status":"0","recid":"75715","relation_version_is_last":true,"title":["Ion temperature profile control system using reinforcement learning technique"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-05-16T00:58:26.265011+00:00"}