Ohkubo Masato 大久保豪人

Researcher Number	40777976
Other IDs
Affiliation (Current)	2025: 東洋大学, 経営学部, 准教授
Affiliation (based on the past Project Information) *help	2022 – 2023: 東洋大学, 経営学部, 准教授 2019 – 2021: 東洋大学, 経営学部, 講師 2018: 早稲田大学, 理工学術院, 助教
Review Section/Research Field	Principal Investigator Basic Section 25010:Social systems engineering-related
Keywords	Principal Investigator マハラノビス・タグチ・システム / 統計的パターン認識 / 高次元主成分分析 / タグチメソッド / 異常検出 / スパース主成分分析 / スパースモデリング / ベキ密度ダイバージェンス / ガンマ・ダイバージェンス / 条件付き異常検出 … More / ガウシアン・グラフィカル・モデリング / MTシステム / スパース・モデリング / ロバスト統計 Less

Development of noise-robust statistical anomaly detection procedures for condition-based maintenancePrincipal Investigator
- Principal Investigator
  
  大久保豪人
- Project Period (FY)
  2021 – 2025
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 25010:Social systems engineering-related
- Research Institution
  Toyo University
Development of practical anomaly detection based on robust sparse modelingPrincipal Investigator
- Principal Investigator
  
  Ohkubo Masato
- Project Period (FY)
  2018 – 2021
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 25010:Social systems engineering-related
- Research Institution
  Toyo University
  Waseda University

All 2023 2022 2021 2020 2019 2018

All Journal Article Presentation

[Journal Article] A Consideration of the Recognition Taguchi Method Using High-Dimensional Principal Component Analysis2023
- Author(s)
  Asano Ryo、Ohkubo Masato、Nagata Yasushi
- Journal Title
  
  Total Quality Science
  
  Volume: 8 Issue: 2 Pages: 70-76
- DOI
  10.17929/tqs.8.70
- ISSN
  2189-3195
- Year and Date
  2023-06-15
- Language
  English
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-21K14372
[Journal Article] The T-method with the application of sparse modeling2023
- Author(s)
  Asano Ryo、Ohkubo Masato、Eguchi Shinto、Nagata Yasushi
- Journal Title
  
  Total Quality Science
  
  Volume: 9 Issue: 1 Pages: 1-7
- DOI
  10.17929/tqs.9.1
- ISSN
  2189-3195
- Year and Date
  2023-10-10
- Language
  English
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K14372, KAKENHI-PROJECT-22K11942
[Journal Article] Mahalanobis-Taguchi Method for Anomaly Detection and Classification2022
- Author(s)
  Honma Kentaro、Ohkubo Masato、Eguchi Shinto、Nagata Yasushi
- Journal Title
  
  Total Quality Science
  
  Volume: 8 Issue: 1 Pages: 1-13
- DOI
  10.17929/tqs.8.1
- ISSN
  2189-3195
- Year and Date
  2022-12-27
- Language
  English
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22K11942, KAKENHI-PROJECT-21K14372, KAKENHI-PROJECT-18H03211
[Journal Article] Anomaly detection for noisy data with the Mahalanobis-Taguchi system2020
- Author(s)
  Masato Okubo and Yasushi Nagata
- Journal Title
  
  Quality Innovation Prosperity
  
  Volume: 24 Issue: 2 Pages: 75-92
- DOI
  10.12776/qip.v24i2.1441
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K11202, KAKENHI-PROJECT-18K13953
[Journal Article] Anomaly detection for unlabelled unit space using the Mahalanobis-Taguchi system2019
- Author(s)
  Masato Ohkubo and Yasushi Nagata
- Journal Title
  
  Total Quality Management & Business Excellence
  
  Volume: - Issue: 5-6 Pages: 1-15
- DOI
  10.1080/14783363.2019.1616542
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-18K13953
[Journal Article] Development of High-dimensional Data Analysis Procedures in Mahalanobis-Taguchi System2019
- Author(s)
  大久保豪人
- Journal Title
  
  Oukan (Journal of Transdisciplinary Federation of Science and Technology)
  
  Volume: 13 Issue: 2 Pages: 117-122
- DOI
  10.11487/trafst.13.2_117
- NAID
  130007730125
- ISSN
  1881-7610, 2189-6399
- Year and Date
  2019-10-15
- Language
  Japanese
- Open Access
- Data Source
  KAKENHI-PROJECT-18K13953
[Journal Article] Conditional anomaly detection based on a latent class model2019
- Author(s)
  Masato Okubo and Yasushi Nagata
- Journal Title
  
  Total Quality Management and Business Excellence
  
  Volume: 30 Issue: sup1 Pages: S227-S239
- DOI
  10.1080/14783363.2019.1665847
- Peer Reviewed / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K11202, KAKENHI-PROJECT-18K13953
[Presentation] Taguchi’s RT method with sparse principal component analysis2023
- Author(s)
  Riku Ohta, Masato Ohkubo, Hiroki Iwamoto, Yasushi Nagata
- Organizer
  Asian Network for Quality (ANQ) Congress 2023
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K14372
[Presentation] The T-method with the application of sparse modeling2022
- Author(s)
  Ryo Asano、Ohkubo Masato、Eguchi Shinto、Nagata Yasushi
- Organizer
  Asian Network for Quality (ANQ) Congress 2022
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K14372
[Presentation] Mahalanobis-Taguchi Method for Anomaly Detection and Classification2021
- Author(s)
  Kentaro Honma, Masato Ohkubo, Yasushi Nagata
- Organizer
  Asian Network for Quality (ANQ) Congress 2021
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K13953
[Presentation] A Consideration of the Recognition Taguchi Method Using High-Dimensional Principal Component Analysis2021
- Author(s)
  Ryo Asano, Masato Ohkubo, Yasushi Nagata
- Organizer
  Asian Network for Quality (ANQ) Congress 2021
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K13953
[Presentation] Discriminant T-method and its application2021
- Author(s)
  Shota NAKAYAMA, Masato OHKUBO, Yasushi NAGATA
- Organizer
  Asian Network for Quality (ANQ) Congress 2021
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K14372
[Presentation] Discriminant T-method and its application2021
- Author(s)
  Shota Nakayama, Masato Ohkubo, Yasushi Nagata
- Organizer
  Asian Network for Quality (ANQ) Congress 2021
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K13953
[Presentation] A Consideration of the Recognition Taguchi Method Using High-Dimensional Principal Component Analysis2021
- Author(s)
  Ryo ASANO, Masato OHKUBO, Yasushi NAGATA
- Organizer
  Asian Network for Quality (ANQ) Congress 2021
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K14372
[Presentation] Mahalanobis-Taguchi Method for Anomaly Detection and Classification2021
- Author(s)
  Kentaro HONMA, Masato OHKUBO, Yasushi NAGATA
- Organizer
  Asian Network for Quality (ANQ) Congress 2021
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K14372
[Presentation] Anomaly detection for noisy data with the Mahalanobis-Taguchi system2019
- Author(s)
  Masato Ohkubo and Yasushi Nagata
- Organizer
  22th QMOD conference on Quality and Service Sciences ICQSS
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K13953
[Presentation] ロバスト・スパース・グラフィカル・モデリングに基づくマハラノビス・タグチ法2019
- Author(s)
  大久保豪人・永田靖
- Organizer
  日本品質管理学会第119回研究発表会
- Data Source
  KAKENHI-PROJECT-18K13953
[Presentation] THE MAHALANOBIS-TAGUCHI SYSTEM BASED ON STATISTICAL MODELING2019
- Author(s)
  Masato Ohkubo
- Organizer
  The Fifth International Conference on the Interface between Statistics and Engineering
- Invited / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K13953
[Presentation] グラフィカル・モデリングに基づくマハラノビス・タグチ法2018
- Author(s)
  大久保豪人
- Organizer
  2018年度統計関連学会連合大会
- Invited
- Data Source
  KAKENHI-PROJECT-18K13953
[Presentation] 潜在クラスモデルに基づくマハラノビス・タグチ法2018
- Author(s)
  大久保豪人・永田靖
- Organizer
  日本品質管理学会第116回研究発表会
- Data Source
  KAKENHI-PROJECT-18K13953
[Presentation] 統計的モデリングに基づくマハラノビス・タグチ・システム2018
- Author(s)
  大久保豪人
- Organizer
  第９回横幹連合コンファレンス
- Invited
- Data Source
  KAKENHI-PROJECT-18K13953
[Presentation] Anomaly detection with Mahalanobis-Taguchi method based on robust sparse graphical modeling2018
- Author(s)
  Masato Ohkubo, Hironori Fujisawa and Yasushi Nagata
- Organizer
  Asian Network for Quality (ANQ) Congress 2018
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K13953
[Presentation] ベイズ的主成分分析を応用したマハラノビス・タグチ法2018
- Author(s)
  大久保豪人・永田靖
- Organizer
  日本品質管理学会第48回年次大会研究発表会
- Data Source
  KAKENHI-PROJECT-18K13953
[Presentation] Conditional anomaly detection based on a latent class model2018
- Author(s)
  Masato Ohkubo and Yasushi Nagata
- Organizer
  21th QMOD conference on Quality and Service Sciences ICQSS
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K13953

1. NAGATA Yasushi

# of Collaborated Projects: 0 results

# of Collaborated Products: 2 results

Ohkubo Masato 大久保 豪人

Research Projects

Research Products

Co-Researchers

Development of noise-robust statistical anomaly detection procedures for condition-based maintenancePrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development of practical anomaly detection based on robust sparse modelingPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] A Consideration of the Recognition Taguchi Method Using High-Dimensional Principal Component Analysis2023

Author(s)

Journal Title

DOI

ISSN

Year and Date

Language

Data Source

[Journal Article] The T-method with the application of sparse modeling2023

Author(s)

Journal Title

DOI

ISSN

Year and Date

Language

Data Source

[Journal Article] Mahalanobis-Taguchi Method for Anomaly Detection and Classification2022

Author(s)

Journal Title

DOI

ISSN

Year and Date

Language

Data Source

[Journal Article] Anomaly detection for noisy data with the Mahalanobis-Taguchi system2020

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Anomaly detection for unlabelled unit space using the Mahalanobis-Taguchi system2019

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Development of High-dimensional Data Analysis Procedures in Mahalanobis-Taguchi System2019

Author(s)

Journal Title

DOI

NAID

ISSN

Year and Date

Language

Data Source

[Journal Article] Conditional anomaly detection based on a latent class model2019

Author(s)

Journal Title

DOI

Data Source

[Presentation] Taguchi’s RT method with sparse principal component analysis2023

Author(s)

Organizer

Data Source

[Presentation] The T-method with the application of sparse modeling2022

Author(s)

Organizer

Data Source

[Presentation] Mahalanobis-Taguchi Method for Anomaly Detection and Classification2021

Author(s)

Organizer

Data Source

[Presentation] A Consideration of the Recognition Taguchi Method Using High-Dimensional Principal Component Analysis2021

Author(s)

Organizer

Data Source

Ohkubo Masato 大久保豪人