中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页
机构
成果
学者
登录
注册
登陆
×
验证码:
换一张
忘记密码?
记住我
×
校外用户登录
CAS IR Grid
机构
烟台海岸带研究所 [2]
自动化研究所 [1]
武汉岩土力学研究所 [1]
采集方式
OAI收割 [4]
内容类型
期刊论文 [4]
发表日期
2025 [1]
2024 [1]
2023 [2]
学科主题
筛选
浏览/检索结果:
共4条,第1-4条
帮助
条数/页:
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
排序方式:
请选择
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
发表日期升序
发表日期降序
Knowledge-Based Machine learning for Real-Time rock strength testing while Drilling: Bridging Simulation and Reality
期刊论文
OAI收割
MEASUREMENT, 2025, 卷号: 246, 页码: 17
作者:
Bai, Jun
;
Wang, Sheng
;
Liu, Liu
;
Xu, Zhengxuan
;
Li, Shaojun
  |  
收藏
  |  
浏览/下载:14/0
  |  
提交时间:2025/06/27
Intelligent Real-time
In-situ Rock Strength Testing
Physics-Informed Machine Learning
Explainable AI Methods
Multi-Scenario Adaptability
Artificial Lateral Line Sensor for Robotic Fish Speed Measurement Based on Surface Flow Field Detection and Turbulence Noise Suppression
期刊论文
OAI收割
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2024, 页码: 14
作者:
Zhang, Zhuoliang
;
Zhou, Chao
;
Cheng, Long
;
Fan, Junfeng
;
Tan, Min
  |  
收藏
  |  
浏览/下载:30/0
  |  
提交时间:2024/09/09
Robot sensing systems
Fish
Robots
Velocity measurement
Noise
Deformation
Calibration
Artificial lateral line
speed of robotic fish
turbulence noise suppression
physics-informed machine learning
flow sensing
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:15/0
  |  
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:34/0
  |  
提交时间:2023/11/15
storm surge prediction
machine learning
hybrid methods
physics-informed neural networks