| Transfer learning Gaussian process regression surrogate model with explainability for structural reliability analysis under variation in uncertainties T Saida, M Nishio Computers & Structures 281, 2023 | 19 | 2023 |
| CNN-based segmentation frameworks for structural component and earthquake damage determinations using UAV images T Saida, M Rashid, Y Nemoto, S Tsukamoto, T Asai, M Nishio Earthquake Engineering and Engineering Vibration 22 (2), 359-369, 2023 | 8 | 2023 |
| Gaussian Process Regression Surrogate Model for Seismic Vulnerability Assessment of Highway Bridge Structure System T Saida, R Muhammad, M Nishio International Conference on Experimental Vibration Analysis for Civil …, 2023 | 1 | 2023 |
| Digital twin framework for real-time dynamic analysis visualization with detecting dynamic changes in structures properties using PINN T Okuda, T Saida, G Matono, M Nishio Sensors and Smart Structures Technologies for Civil, Mechanical, and …, 2023 | 1 | 2023 |
| Construction of gaussian process regression surrogate model for nonlinear seismic response analysis using ard kernel T Saida, M Nishio Journal of Japan Society of Civil Engineers, Ser. A2 (Applied Mechanics (AM …, 2021 | 1 | 2021 |
| System fragility analysis of highway bridge using multi-output Gaussian process regression surrogate model T Saida, M Rashid, M Nishio Advances in Structural Engineering, 13694332241291255, 2024 | | 2024 |
| TL-GPRSM: A python software for constructing transfer learning Gaussian process regression surrogate model with explainability T Saida, M Nishio Software Impacts 16, 100515, 2023 | | 2023 |
| Gaussian process regression surrogate model for dynamic analysis to account for uncertainties in seismic loading T Saida, M Nishio Sensors and Smart Structures Technologies for Civil, Mechanical, and …, 2023 | | 2023 |
| ARD カーネルによる非線形地震応答解析のガウス過程回帰代替モデル構築 才田大聖， 西尾真由子 土木学会論文集 A2 (応用力学) 77 (2), I_93-I_104, 2021 | | 2021 |
Mayuko NISHIOUniversity of TsukubaVerified email at kz.tsukuba.ac.jp
