Bezier Curve-Based Shape Knowledge Acquisition and Fusion for Surrogate Model Construction

Peng An*, Wenbin Ye, Zizhao Wang, Hua Xiao, Yongsong Long, Jia Hao

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Surrogate model technology is a key technology in the field of engineering design with limited data. Fusion of engineering knowledge into surrogate models is an effective method to improve the prediction accuracy. However, engineering knowledge in this field describes the complex relationship between variables, which makes it difficult to obtain quantitative knowledge. Therefore, the engineering knowledge acquisition and fusion technology based on Bezier Curve for complex equipment design was proposed, which covered the entire process from knowledge acquisition to filtering and fusion. Finally, through the verification of the Unmanned Vehicle Truss design case and test functions, the experimental results show that the technology can achieve the effective acquisition of complex curve knowledge and represent multi-knowledge information effectively.

源语言英语
主期刊名Proceedings of the Future Technologies Conference, FTC 2022, Volume 1
编辑Kohei Arai
出版商Springer Science and Business Media Deutschland GmbH
328-342
页数15
ISBN(印刷版)9783031184604
DOI
出版状态已出版 - 2023
活动7th Future Technologies Conference, FTC 2022 - Vancouver, 加拿大
期限: 20 10月 202221 10月 2022

出版系列

姓名Lecture Notes in Networks and Systems
559 LNNS
ISSN(印刷版)2367-3370
ISSN(电子版)2367-3389

会议

会议7th Future Technologies Conference, FTC 2022
国家/地区加拿大
Vancouver
时期20/10/2221/10/22

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