ログイン
言語:

WEKO3

  • トップ
  • ランキング
To
lat lon distance
To

Field does not validate



インデックスリンク

インデックスツリー

メールアドレスを入力してください。

WEKO

One fine body…

WEKO

One fine body…

アイテム

{"_buckets": {"deposit": "728b7ea2-15f0-45aa-afd3-c7722dac67d6"}, "_deposit": {"id": "22973", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "22973"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00022973", "sets": ["675"]}, "author_link": ["67837", "67838", "67839"], "item_10_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2016-08", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "66", "bibliographicPageStart": "54", "bibliographicVolumeNumber": "47", "bibliographic_titles": [{"bibliographic_title": "Transportation Research Part D: Transport and Environment", "bibliographic_titleLang": "en"}]}]}, "item_10_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "In this research, a Bayesian network (BN) approach is proposed to model the car use behavior of drivers by time of day and to analyze its relationship with driver and car characteristics. The proposed BN model can be categorized as a tree-augmented naive (TAN) Bayesian network. A latent class variable is included in this model to describe the unobserved heterogeneity of drivers. Both the structure and the parameters are learned from the dataset, which is extracted from GPS data collected in Toyota City, Japan. Based on inferences and evidence sensitivity analysis using the estimated TAN model, the effects of each single observed characteristic on car use measures are tested and found to be significant. The features of each category of the latent class are also analyzed. By testing the effect of each car use measure on every other measure, it is found that the correlations between car use measures are significant and should be considered in modeling car use behavior.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "DOI", "subitem_identifier_uri": "http://dx.doi.org/10.1016/j.trd.2016.04.011"}, {"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/25154"}]}, "item_10_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "Elsevier", "subitem_publisher_language": "en"}]}, "item_10_relation_11": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type": "isVersionOf", "subitem_relation_type_id": {"subitem_relation_type_id_text": "https://doi.org/10.1016/j.trd.2016.04.011", "subitem_relation_type_select": "DOI"}}]}, "item_10_rights_12": {"attribute_name": "権利", "attribute_value_mlt": [{"subitem_rights": "© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/", "subitem_rights_language": "en"}]}, "item_10_select_15": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_select_item": "author"}]}, "item_10_source_id_7": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "1361-9209", "subitem_source_identifier_type": "PISSN"}]}, "item_1615787544753": {"attribute_name": "出版タイプ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_ab4af688f83e57aa", "subitem_version_type": "AM"}]}, "item_access_right": {"attribute_name": "アクセス権", "attribute_value_mlt": [{"subitem_access_right": "open access", "subitem_access_right_uri": "http://purl.org/coar/access_right/c_abf2"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Li, Dawei", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "67837", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Miwa, Tomio", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "67838", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Morikawa, Takayuki", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "67839", "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": "2018-08-01"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "Li_Miwa_Morikawa_partD2016.pdf", "filesize": [{"value": "467.2 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_note", "mimetype": "application/pdf", "size": 467200.0, "url": {"label": "Li_Miwa_Morikawa_partD2016.pdf ファイル公開:2018/08/01", "objectType": "fulltext", "url": "https://nagoya.repo.nii.ac.jp/record/22973/files/Li_Miwa_Morikawa_partD2016.pdf"}, "version_id": "5e0eff74-5e55-4ef3-8d3a-d1b89a4204c6"}]}, "item_keyword": {"attribute_name": "キーワード", "attribute_value_mlt": [{"subitem_subject": "Car use", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Bayesian networks", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Latent class", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Machine learning", "subitem_subject_scheme": "Other"}, {"subitem_subject": "GPS data", "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": "Modeling time-of-day car use behavior: A Bayesian network approach", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Modeling time-of-day car use behavior: A Bayesian network approach", "subitem_title_language": "en"}]}, "item_type_id": "10", "owner": "1", "path": ["675"], "permalink_uri": "http://hdl.handle.net/2237/25154", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2016-12-07"}, "publish_date": "2016-12-07", "publish_status": "0", "recid": "22973", "relation": {}, "relation_version_is_last": true, "title": ["Modeling time-of-day car use behavior: A Bayesian network approach"], "weko_shared_id": -1}
  1. F200 未来材料・システム研究所
  2. F200a 雑誌掲載論文
  3. 学術雑誌

Modeling time-of-day car use behavior: A Bayesian network approach

http://hdl.handle.net/2237/25154
http://hdl.handle.net/2237/25154
4fea748e-9724-49c8-960f-3fb00774b22f
名前 / ファイル ライセンス アクション
Li_Miwa_Morikawa_partD2016.pdf Li_Miwa_Morikawa_partD2016.pdf ファイル公開:2018/08/01 (467.2 kB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2016-12-07
タイトル
タイトル Modeling time-of-day car use behavior: A Bayesian network approach
言語 en
著者 Li, Dawei

× Li, Dawei

WEKO 67837

en Li, Dawei

Search repository
Miwa, Tomio

× Miwa, Tomio

WEKO 67838

en Miwa, Tomio

Search repository
Morikawa, Takayuki

× Morikawa, Takayuki

WEKO 67839

en Morikawa, Takayuki

Search repository
アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利
言語 en
権利情報 © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
キーワード
主題Scheme Other
主題 Car use
キーワード
主題Scheme Other
主題 Bayesian networks
キーワード
主題Scheme Other
主題 Latent class
キーワード
主題Scheme Other
主題 Machine learning
キーワード
主題Scheme Other
主題 GPS data
抄録
内容記述 In this research, a Bayesian network (BN) approach is proposed to model the car use behavior of drivers by time of day and to analyze its relationship with driver and car characteristics. The proposed BN model can be categorized as a tree-augmented naive (TAN) Bayesian network. A latent class variable is included in this model to describe the unobserved heterogeneity of drivers. Both the structure and the parameters are learned from the dataset, which is extracted from GPS data collected in Toyota City, Japan. Based on inferences and evidence sensitivity analysis using the estimated TAN model, the effects of each single observed characteristic on car use measures are tested and found to be significant. The features of each category of the latent class are also analyzed. By testing the effect of each car use measure on every other measure, it is found that the correlations between car use measures are significant and should be considered in modeling car use behavior.
言語 en
内容記述タイプ Abstract
出版者
言語 en
出版者 Elsevier
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ AM
出版タイプResource http://purl.org/coar/version/c_ab4af688f83e57aa
DOI
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1016/j.trd.2016.04.011
ISSN
収録物識別子タイプ PISSN
収録物識別子 1361-9209
書誌情報 en : Transportation Research Part D: Transport and Environment

巻 47, p. 54-66, 発行日 2016-08
著者版フラグ
値 author
URI
識別子 http://dx.doi.org/10.1016/j.trd.2016.04.011
識別子タイプ DOI
URI
識別子 http://hdl.handle.net/2237/25154
識別子タイプ HDL
戻る
0
views
See details
Views

Versions

Ver.1 2021-03-01 14:45:14.035150
Show All versions

Share

Mendeley Twitter Facebook Print Addthis

Cite as

エクスポート

OAI-PMH
  • OAI-PMH JPCOAR
  • OAI-PMH DublinCore
  • OAI-PMH DDI
Other Formats
  • JSON
  • BIBTEX

Confirm


Powered by WEKO3


Powered by WEKO3