机构

• 数学与系统科学研究院 [5]
• 力学研究所 [3]
• 金属研究所 [2]
• 烟台海岸带研究所 [2]
• 海洋研究所 [1]
• 云南天文台 [1]
• 更多

采集方式

• OAI收割 [15]

内容类型

• 期刊论文 [13]
• CNKI期刊论文 [1]
• 会议论文 [1]

发表日期

• 2025 [4]
• 2024 [2]
• 2023 [2]
• 2022 [4]
• 2021 [3]

学科主题

• 天文学 [1]
• 天文学::天体测量学 [1]

筛选

浏览/检索结果: 共15条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择发表日期升序发表日期降序题名升序题名降序提交时间升序提交时间降序作者升序作者降序 Perturbation Orbit Prediction Method Based on Physics-Informed ResNet 会议论文  OAI收割 Harbin, China, 2025-08-02 作者:  Zhao, Meng;  Shu P(舒鹏);  Yang, Zhen;  Luo, Yazhong   |  收藏  |  浏览/下载：4/0  |  提交时间：2026/01/12 Orbit Prediction  Two  Body Orbital Dynamics  J2 Perturbation  Physics  Informed Neural Networks (PINNs)  Residual Neural Network (ResNet)  Automatic Differentiation   Three-dimensional seepage analysis for the tunnel in nonhomogeneous porous media with physics-informed deep learning 期刊论文  OAI收割 ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS, 2025, 卷号: 175, 页码: 12 作者:  Lin, Shan;  Dong, Miao;  Luo, Hongming;  Guo, Hongwei;  Zheng, Hong   |  收藏  |  浏览/下载：33/0  |  提交时间：2025/06/27 Physics-informed deep learning  Tunnel  Neural networks  Seepage  Nonhomogeneous porous media   Sparse wavefield reconstruction based on Physics-Informed neural networks 期刊论文  OAI收割 ULTRASONICS, 2025, 卷号: 149, 页码: 12 作者:  Xu, Bin;  Zou, Yun;  Sha, Gaofeng;  Yang, Liang;  Cai, Guixi   |  收藏  |  浏览/下载：5/0  |  提交时间：2025/04/27 Physics-Informed Neural Networks  Wavefield Reconstruction  Laser Ultrasonic  Non-destructive Testing   Direct numerical simulation of natural convection based on parameter-input physics-informed neural networks 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 2025, 卷号: 236, 页码: 126379 作者:  Ye,Shuran;  Huang JL(黄剑霖);  Zhang, Zhen;  Wang YW(王一伟);  Huang CG(黄晨光)   |  收藏  |  浏览/下载：50/0  |  提交时间：2024/12/02 Natural convection  Physics-informed neural networks  Parameter-input PINNs  Ra number  Deep learning   Leveraging physics-informed neural networks for wavefield analysis in laser ultrasonic testing 期刊论文  OAI收割 NONDESTRUCTIVE TESTING AND EVALUATION, 2024, 页码: 23 作者:  Li, Yang;  Xu, Bin;  Zou, Yun;  Sha, Gaofeng;  Cai, Guixi   |  收藏  |  浏览/下载：3/0  |  提交时间：2025/04/27 Physics-informed neural networks  wavefield reconstruction  wavefield prediction  laser ultrasonic  non-destructive testing   AsPINN: Adaptive symmetry-recomposition physics-informed neural networks 期刊论文  OAI收割 COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2024, 卷号: 432, 页码: 34 作者:  Liu ZT(刘子提);  Liu Y(刘洋);  Yan, Xunshi;  Liu W(刘文);  Guo SQ(郭帅旗)   |  收藏  |  浏览/下载：50/0  |  提交时间：2024/11/01 Network structure  Parameter-sharing  Feature-enhanced physics-informed neural  networks  Symmetry decomposition   A Review of Application of Machine Learning in Storm Surge Problems 期刊论文  OAI收割 JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2023, 卷号: 11, 期号: 9, 页码: 35 作者:  Qin, Yue;  Su, Changyu;  Chu, Dongdong;  Zhang, Jicai;  Song, Jinbao   |  收藏  |  浏览/下载：36/0  |  提交时间：2024/11/02 storm surge prediction  machine learning  hybrid methods  physics-informed neural networks   A Review of Application of Machine Learning in Storm Surge Problems 期刊论文  OAI收割 JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2023, 卷号: 11, 期号: 9, 页码: 35 作者:  Qin, Yue;  Su, Changyu;  Chu, Dongdong;  Zhang, Jicai;  Song, Jinbao   |  收藏  |  浏览/下载：62/0  |  提交时间：2023/11/15 storm surge prediction  machine learning  hybrid methods  physics-informed neural networks   Monte Carlo fPINNs: Deep learning method for forward and inverse problems involving high dimensional fractional partial differential equations 期刊论文  OAI收割 COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2022, 卷号: 400, 页码: 17 作者:  Guo, Ling;  Wu, Hao;  Yu, Xiaochen;  Zhou, Tao   |  收藏  |  浏览/下载：71/0  |  提交时间：2023/02/07 Physics -informed neural networks  Fractional Laplacian  Nonlocal operators  Uncertainty quantification   Physics-informed deep-learning parameterization of ocean vertical mixing improves climate simulations CNKI期刊论文  OAI收割 2022 作者:  Yuchao Zhu;  Rong-Hua Zhang;  James N.Moum;  Fan Wang;  Xiaofeng Li   |  收藏  |  浏览/下载：25/0  |  提交时间：2024/12/18 physics-informed deep learning  climate model biases  ocean vertical-mixing parameterizations  long-term turbulence data  artificial neural networks under physics constraint