{"_buckets": {"deposit": "71a54e49-966e-4d99-8785-54b678caa2ec"}, "_deposit": {"id": "3345", "owners": [1], "pid": {"revision_id": 0, "type": "depid", "value": "3345"}, "status": "published"}, "_oai": {"id": "oai:nied-repo.bosai.go.jp:00003345", "sets": []}, "author_link": [], "item_10001_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2022-09-14", "bibliographicIssueDateType": "Issued"}, "bibliographic_titles": [{"bibliographic_title": "第38回 ファジィ システム シンポジウム / FSS2022", "bibliographic_titleLang": "ja"}]}]}, "item_10001_description_5": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "In this paper, we study an anomaly detection method for human flow which is significantly\ndifferent from normal cases due to accidents or natural disasters. Human flow can be assumed to have typical patterns such as going to work and leaving work in the daily life of the people. Developing an anomaly detection method can lead to the discovery of the hidden cause. In this paper, we study a method which aims to detect anomalies in human flow, taking as an example in operation status of railways. We confirmed that our method detects actual suspension of operations.", "subitem_description_language": "ja", "subitem_description_type": "Other"}, {"subitem_description": "In this paper, we study an anomaly detection method for human flow which is significantly\ndifferent from normal cases due to accidents or natural disasters. Human flow can be assumed to have typical patterns such as going to work and leaving work in the daily life of the people. Developing an anomaly detection method can lead to the discovery of the hidden cause. In this paper, we study a method which aims to detect anomalies in human flow, taking as an example in operation status of railways. We confirmed that our method detects actual suspension of operations.", "subitem_description_language": "en", "subitem_description_type": "Other"}]}, "item_10001_publisher_8": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "日本知能情報ファジィ学会", "subitem_publisher_language": "ja"}]}, "item_10001_relation_14": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type_id": {"subitem_relation_type_id_text": "10.14864/fss.38.0_114"}}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Kim SeongIn", "creatorNameLang": "ja"}]}, {"creatorNames": [{"creatorName": "澁谷 長史", "creatorNameLang": "ja"}]}, {"creatorNames": [{"creatorName": "取出 新吾", "creatorNameLang": "ja"}]}, {"creatorNames": [{"creatorName": "遠藤 靖典", "creatorNameLang": "ja"}]}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "jpn"}]}, "item_title": "人流データに基づく鉄道運行状況の異常検知手法の基礎的検討", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "人流データに基づく鉄道運行状況の異常検知手法の基礎的検討", "subitem_title_language": "ja"}, {"subitem_title": "A Fundamental Study of Anomaly Detection Method for Railway Operation Status Based on Human Flow Data", "subitem_title_language": "en"}]}, "item_type_id": "40001", "owner": "1", "path": ["1670839190650"], "permalink_uri": "https://nied-repo.bosai.go.jp/records/3345", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2023-07-24"}, "publish_date": "2023-07-24", "publish_status": "0", "recid": "3345", "relation": {}, "relation_version_is_last": true, "title": ["人流データに基づく鉄道運行状況の異常検知手法の基礎的検討"], "weko_shared_id": -1}