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Summary & Details

An Inverse Design Method for Windshield Defrosting-Demisting Performance Using Machine Learning Techniques

機械学習を活用したデフロスタ晴れ性能の逆解析技術の開発

Delivery: Available on this site

Format: PDF

Price: Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880

Publication code: 20224087

Paper/Info type: Symposium Text

No.16-21

Pages: 1-32(Total 32 p)

Date of publication: Jan 2022

Publisher: JSAE

Language: Japanese

Event: JSAE Symposium 2021

Detailed Information

Category(J)	PPT資料 Translation
Category(E)	PPT slides
Author(J)	1) ファンビンロン, 2) 田中博
Author(E)	1) Phan Vinh Long, 2) Tanaka Hiroshi
Affiliation(J)	1) トヨタ自動車株式会社, 2) トヨタシステムズ
Affiliation(E)	1) Toyota Motor Corporation, 2) Toyota Systems
Abstract(J)	本研究では機械学習を活用してデフロスタ晴れ性能を表すウィンドシルード流速分布を幅広い設計空間の中で瞬時に予測可能なReduced Modelを作成した。又Reduced Modelの予測結果に対して決定木アルゴリズムを活用したデフロスタ晴れ性能成立条件探索技術（逆解析技術）を構築した。 Translation

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