{"created":"2023-05-15T14:20:04.014320+00:00","id":48,"links":{},"metadata":{"_buckets":{"deposit":"6a0b0208-b892-4f55-99e6-3b5477fbd926"},"_deposit":{"created_by":6,"id":"48","owners":[6],"pid":{"revision_id":0,"type":"depid","value":"48"},"status":"published"},"_oai":{"id":"oai:ptu.repo.nii.ac.jp:00000048","sets":[]},"author_link":["139","140"],"control_number":"48","item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2019","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicPageEnd":"42","bibliographicPageStart":"36","bibliographicVolumeNumber":"35","bibliographic_titles":[{"bibliographic_title":"技能科学研究"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Particle Swarm Optimization (PSO) is one of the population\nbased metaheuristics. The algorithm is simple yet the\nconvergence is rather fast. The parameter values have a large influence on the search performance. Many studies on\nPSO parameter tuning have been conducted so far. This paper proposes determining parameters separately in eac h\nstage into which the iterative process is divided, using Design of Experiments (DoE) methodology. The situation of\nthe swarm is considered to be changing as the process proceeds. Hence, a certain effect is expected with this\nmethod. The exploration with the proposed method is performed on four test functions. Additionally the exploration\nwith three other methods is also conducted for comparison. The proposed method yields good results. This study\nalso reveals that the search performance improves when para meters, such as inertia weight, increase as the process\nproceeds.","subitem_description_type":"Abstract"}]},"item_10001_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2434-3706","subitem_source_identifier_type":"ISSN"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"印南　, 信男"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Innami, Michio","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-08-21"}],"displaytype":"detail","filename":"r7 論文08印南_2.pdf","filesize":[{"value":"757.5 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"【論文】Optimization of PSO by Determining Parameters for Multiple Stages with DoE","url":"https://ptu.repo.nii.ac.jp/record/48/files/r7 論文08印南_2.pdf"},"version_id":"16270816-83ab-4e6d-ba41-90dc43fda45d"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Metaheuristics","subitem_subject_scheme":"Other"},{"subitem_subject":"PSO","subitem_subject_scheme":"Other"},{"subitem_subject":"Search performance","subitem_subject_scheme":"Other"},{"subitem_subject":"Parameter tuning","subitem_subject_scheme":"Other"},{"subitem_subject":"DoE","subitem_subject_scheme":"Other"},{"subitem_subject":"Metaheuristics","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"PSO","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Search performance","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Parameter tuning","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"DoE","subitem_subject_language":"en","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":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"【論文】Optimization of PSO by Determining Parameters for Multiple Stages with DoE","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"【論文】Optimization of PSO by Determining Parameters for Multiple Stages with DoE","subitem_title_language":"ja"},{"subitem_title":"Optimization of PSO by Determining Parameters for Multiple Stages with DoE","subitem_title_language":"en"}]},"item_type_id":"10001","owner":"6","path":["18"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2020-01-10"},"publish_date":"2020-01-10","publish_status":"0","recid":"48","relation_version_is_last":true,"title":["【論文】Optimization of PSO by Determining Parameters for Multiple Stages with DoE"],"weko_creator_id":"6","weko_shared_id":-1},"updated":"2023-06-22T03:13:54.850532+00:00"}