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Updated: Jan 13, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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Published on: March 2, 2015

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一个以物理为基础的神经网络架构,用于科学和工程中的移动边界问题

Sanchita Malla1, Dietmar Oelz2, Sitikantha Roy3

  • 1UQ-IITD Academy of Research (UQIDAR), Indian Institute of Technology, Delhi New Delhi, 110016, India; School of Mathematics and Physics, University of Queensland, 4072, QLD, Australia; Department of Applied Mechanics, Indian Institute of Technology, Delhi New Delhi, 110016, India.

Neural networks : the official journal of the International Neural Network Society
|January 7, 2026
PubMed
概括

本研究介绍了一种新的物理信息神经网络 (PINN) 架构,用于解决复杂的移动边界问题. 新的PINN方法有效地处理不断变化的空间领域,为科学和工程提供强大的模拟平台.

关键词:
深度学习是一种深度学习.移动边界问题 移动边界问题神经网络的架构神经网络的架构基于物理学的神经网络.

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