@article{ref1,
title="Development of the robust design method for crash analysis - visualization of conditions for good quality by using pattern recognition and machine learning -",
journal="Transactions of Society of Automotive Engineers of Japan",
year="2022",
author="Sugano, Chitoshi and Tamura, Yoichi and Komamura, Tatsuya",
volume="53",
number="2",
pages="258-263",
abstract="This paper describes a methodology for robust design in crash analysis. We organized a series of robust design processes for crash analysis and showed that it is possible to classify/predict deformation patterns, judge whether they are good or not, identify contributing parameters by applying statistical/machine learning methods in each process. By using a prediction model as a surrogate model, we achieved an extensive search in the design space in a short time.   ===  衝突解析における一連のロバスト設計プロセスを整理し，統計/機械学習を用いた変形パターンの分類/予測，良否判定，寄与因子の特定が可能であることを示した．<p /> <p>Language: ja</p>",
language="ja",
issn="0287-8321",
doi="10.11351/jsaeronbun.53.258",
url="http://dx.doi.org/10.11351/jsaeronbun.53.258"
}