本資料は、掲載誌(URI)等のリンク先にある学位授与機関のWebサイトやCiNii Dissertationsから、本文を自由に閲覧できる場合があります。
Enhancing Tunnel Boring Machine Performance Prediction and Optimization with Artificial Intelligence Models: Insights from Operational Data
Available in National Diet Library
Find on the publisher's website
国立国会図書館デジタルコレクション
Digital data available
Check on the publisher's website
DOI[10.20569/0002000297]to the data of the same series
Search by Bookstore
Read this material in an accessible format.
Holdings of Libraries in Japan
This page shows libraries in Japan other than the National Diet Library that hold the material.
Please contact your local library for information on how to use materials or whether it is possible to request materials from the holding libraries.
other
Akita University Institutional Repository
DigitalYou can check the holdings of institutions and databases with which Institutional Repositories DataBase(IRDB)(Institutional Repository) is linked at the site of Institutional Repositories DataBase(IRDB)(Institutional Repository).
Search by Bookstore
Read in Disability Resources
- Other Services
Bibliographic Record
You can check the details of this material, its authority (keywords that refer to materials on the same subject, author's name, etc.), etc.
- Material Type
- 博士論文
- Author/Editor
- KILIC, KURSAT
- Author Heading
- Publication Date
- 2024-03
- Publication Date (W3CDTF)
- 2024-03
- Alternative Title
- 人工知能モデルによるトンネルボーリングマシンのパフォーマンス予測と最適化の強化: 運用データからの洞察
- Degree grantor/type
- 秋田大学
- Date Granted
- 2024-03-22
- Date Granted (W3CDTF)
- 2024-03-22