{"created":"2023-05-15T12:36:03.965255+00:00","id":936,"links":{},"metadata":{"_buckets":{"deposit":"e7d35803-a404-4c73-9a55-a1401de6eedc"},"_deposit":{"created_by":2,"id":"936","owners":[2],"pid":{"revision_id":0,"type":"depid","value":"936"},"status":"published"},"_oai":{"id":"oai:kutarr.kochi-tech.ac.jp:00000936","sets":["16:21"]},"author_link":["2512"],"item_5_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2009-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"5","bibliographic_titles":[{"bibliographic_title":"Society for Social Management Systems Internet Journal"}]}]},"item_5_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"We usually decide maintenance scenario by minimized life cycle cost from deterioration prediction when we make the bridge maintenance budget plan. There are two types of deterioration prediction, which is graph type and condition transition type. Each type of prediction has a precondition and a characteristic, However, it is often that each prediction is not had a good command of well. In this study, we arrange characteristic of two deterioration predictions, and compare the way of calculation of LCC, and we make the phase of suitable scene and precondition clear. Next, we calculate the LCC of each deterioration predictions for the bridge, and we consider the influence that the difference of the deterioration prediction type gives to the maintenance management budget plan.","subitem_description_type":"Abstract"}]},"item_5_publisher_36":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Society for Social Management Systems"}]},"item_5_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2432-552X","subitem_source_identifier_type":"ISSN"}]},"item_5_version_type_19":{"attribute_name":"著者版フラグ","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":"Yasuda, Keiichi"}],"nameIdentifiers":[{"nameIdentifier":"2512","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":"2019-02-13"}],"displaytype":"detail","filename":"SMS09-105.pdf","filesize":[{"value":"562.9 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"SMS09-105.pdf","url":"https://kutarr.kochi-tech.ac.jp/record/936/files/SMS09-105.pdf"},"version_id":"b87d275e-45c0-4a06-8198-e6cc33b3fe79"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"deterioration curve of graph type","subitem_subject_scheme":"Other"},{"subitem_subject":"deterioration curve of state transition type","subitem_subject_scheme":"Other"},{"subitem_subject":"maintenance plan","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":"conference paper","resourceuri":"http://purl.org/coar/resource_type/c_5794"}]},"item_title":"The influence that the Type of the Deterioration Prediction in Bridge Gives to a Maintenance Budget Plan","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"The influence that the Type of the Deterioration Prediction in Bridge Gives to a Maintenance Budget Plan"}]},"item_type_id":"5","owner":"2","path":["21"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-02-06"},"publish_date":"2018-02-06","publish_status":"0","recid":"936","relation_version_is_last":true,"title":["The influence that the Type of the Deterioration Prediction in Bridge Gives to a Maintenance Budget Plan"],"weko_creator_id":"2","weko_shared_id":-1},"updated":"2023-05-15T13:21:26.548197+00:00"}