積層ゴム支承の終局特性に関する実験及び解析的研究（その５）：フレア状構造を適用した天然ゴム系積層ゴム支承における機械学習を用いたサロゲートモデルによる座屈特性予測

抄録

In the previous study, the author proposed a new flare-like structure with the aim of improving buckling property, and evaluated the ultimate properties of a high-damping rubber bearing with the proposed structure. In the case of a flare-like structure, the structure is more complex than conventional structures, resulting in more design parameters. In recent years, machine learning has drawn attention as a method for predicting the characteristics of products with many parameters. In this study, a method for predicting the buckling property of natural rubber bearings using machine learning is proposed.