分解
发表于 2025-3-25 04:28:23
2191-5644 s.Deep Learning Gaussian Process Analysis.Real-time Video-based Analysis.Applications to Nonlinear Dynamics and Damage Detection.High-rate Structural Monitoring and Prognostics.978-3-031-04124-2978-3-031-04122-8Series ISSN 2191-5644 Series E-ISSN 2191-5652
心神不宁
发表于 2025-3-25 07:41:29
http://reply.papertrans.cn/27/2632/263128/263128_22.png
食物
发表于 2025-3-25 15:11:46
https://doi.org/10.1007/978-3-319-16598-1 geometry, from simple rigid transformations to fibre bundles. The main aim of the chapter is to consider similarity in data using distance metrics with a special focus on transfer learning and data standardisation/normalisation.
laparoscopy
发表于 2025-3-25 19:04:36
http://reply.papertrans.cn/27/2632/263128/263128_24.png
多余
发表于 2025-3-25 22:21:34
http://reply.papertrans.cn/27/2632/263128/263128_25.png
Ibd810
发表于 2025-3-26 02:56:21
On Aspects of Geometry in SHM and Population-Based SHM, geometry, from simple rigid transformations to fibre bundles. The main aim of the chapter is to consider similarity in data using distance metrics with a special focus on transfer learning and data standardisation/normalisation.
航海太平洋
发表于 2025-3-26 05:36:29
Input Estimation of Four-DOF Nonlinear Building Using Probabilistic Recurrent Neural Network, frame building with elastic perfectly plastic springs is considered to evaluate the applicability of the proposed input estimation method to nonlinear dynamic systems. The performance of the network is evaluated on fifteen testing ground motions, and the input estimation is accomplished with high accuracy.
integral
发表于 2025-3-26 11:23:04
http://reply.papertrans.cn/27/2632/263128/263128_28.png
星球的光亮度
发表于 2025-3-26 16:08:21
http://reply.papertrans.cn/27/2632/263128/263128_29.png
引起痛苦
发表于 2025-3-26 16:50:34
Deep Reinforcement Learning for Active Structure Stabilization,une, they can struggle to control high-order underactuated systems (which any high-fidelity structure model is guaranteed to be), and they rely on simple formulations of error or cost to minimize. Reinforcement learning provides a framework to learn high-performance control strategies directly from