Average Weight based Fine-Tuningを活用した熱境界サロゲートモデルの効率的な改良手法の開発

• Material Type: 記事
• Title: Average Weight based Fine-Tuningを活用した熱境界サロゲートモデルの効率的な改良手法の開発
• Volume: 56; 3
• Author/Editor: 下川 智史; 上村 充範; 川口 則雄; 高橋 政克; 餅原 隆浩
• Author Heading: 下川 智史; Shimokawa Tomofumi; 上村 充範; Kamimura Mitsunori; 川口 則雄; Kawaguchi Norio; 高橋 政克; Takahashi Masakatsu; 餅原 隆浩; Mochihara Takahiro
• Publication Date: 2025
• Publication Date (W3CDTF): 2025
• Alternative Title: Development of an Efficient Improvement Method for Thermal Boundary Surrogate Models using Average Weight based Fine-Tuning
• Periodical title: 自動車技術会論文集; Transactions of Society of Automotive Engineers of Japan
• No. or year of volume/issue: 56 3
• Volume: 56
• Issue: 3
• Pages: 471-475
• ISSN (Periodical Title): 0287-8321; 1883-0811
• Alias of Author: Shimokawa Tomofumi; Kamimura Mitsunori; Kawaguchi Norio; Takahashi Masakatsu; Mochihara Takahiro
• Subject Heading: Heat・Fluid; Modeling; Surrogate model; Deep Learning; Transfer Learning; Fine-Tuning; CAE
• Target Audience: 一般
• DOI: 10.11351/jsaeronbun.56.471
• Access Restrictions: インターネット公開
• Data Provider (Database): 科学技術振興機構 : J-STAGE; http://www.jstage.jst.go.jp

• Summary, etc.: Data-driven approaches using machine learning methods are gaining attention as substitutes for Computer-Aided Engineering (CAE). These methods perform...