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Predicting Aquaculture Water Quality Using Machine Learning Approaches
期刊论文
WATER, 2022, 卷号: 14, 期号: 18, 页码: 15
作者:
Li, Tingting
;
Lu, Jian
;
Wu, Jun
;
Zhang, Zhenhua
;
Chen, Liwei
收藏
  |  
浏览/下载:27/0
  |  
提交时间:2022/11/07
industrial aquaculture
machine learning
support vector machine
water quality prediction
Predicting Aquaculture Water Quality Using Machine Learning Approaches
期刊论文
WATER, 2022, 卷号: 14, 期号: 18, 页码: 15
作者:
Li, Tingting
;
Lu, Jian
;
Wu, Jun
;
Zhang, Zhenhua
;
Chen, Liwei
收藏
  |  
浏览/下载:15/0
  |  
提交时间:2022/11/07
industrial aquaculture
machine learning
support vector machine
water quality prediction
Adaptive Finite-Time Control Scheme for Teleoperation With Time-Varying Delay and Uncertainties
期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 卷号: 52, 期号: 3, 页码: 1552-1566
作者:
Zhang, Haochen
;
Song, Aiguo
;
Li, Huijun
;
Chen, Dapeng
;
Fan, Liqiang
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  |  
浏览/下载:13/0
  |  
提交时间:2022/04/21
Force
Robots
Uncertainty
Adaptation models
Delays
Adaptive control
Torque
Adaptive control
communication delay
finite-time control
position
force tracking
teleoperation
Medical image fusion via discrete stationary wavelet transform and an enhanced radial basis function neural network
期刊论文
Applied Soft Computing, 2022, 卷号: 118, 页码: 1-13
作者:
Chao, Zhen
;
Duan, Xingguang
;
Jia, Shuangfu
;
Guo, Xuejun
;
Liu H(刘浩)
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  |  
浏览/下载:19/0
  |  
提交时间:2022/03/07
Discrete stationary wavelet transform
Enhanced radial basis function neural network
Medical image fusion
Adaptive Fault-tolerant Control for Trajectory Tracking and Rectification of Directional Drilling
期刊论文
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2022, 卷号: 20, 期号: 1, 页码: 334-348
作者:
Zhang, Chi
;
Zou, Wei
;
Cheng, Ningbo
;
Gao, Junshan
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  |  
浏览/下载:29/0
  |  
提交时间:2022/03/17
Fault-tolerant control (FTC)
integral sliding mode control (ISMC)
neural network (NN)
nonlinear control system
reinforcement learning (RL)
Adaptive local approximation neural network control based on extraordinariness particle swarm optimization for robotic manipulators
期刊论文
Journal of Mechanical Science and Technology, 2022, 卷号: 36, 期号: 3, 页码: 1469-1483
作者:
H. Y. Sai
;
Z. B. Xu
;
C. Xu
;
X. M. Wang
;
K. Wang and L. Zhu
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  |  
浏览/下载:0/0
  |  
提交时间:2023/06/14
基于RBF神经网络-信息量耦合模型的滑坡易发性评价——以甘肃岷县为例
期刊论文
中国地质灾害与防治学报, 2021, 卷号: 32, 期号: 06, 页码: 116-126
作者:
黄立鑫
;
郝君明
;
李旺平
;
周兆叶
;
贾佩钱
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  |  
浏览/下载:4/0
  |  
提交时间:2022/03/04
滑坡
易发性评价
RBF神经网络
信息量
岷县
Neural Control of Robot Manipulators With Trajectory Tracking Constraints and Input Saturation
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 9, 页码: 4231-4242
作者:
Yang, Chenguang
;
Huang, Dianye
;
He, Wei
;
Cheng, Long
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  |  
浏览/下载:73/0
  |  
提交时间:2021/11/03
Manipulators
Lyapunov methods
Robot kinematics
Trajectory tracking
Automation
Barrier Lyapunov function (BLF)
constrained control
input saturation
robot manipulator
Force Sensorless Admittance Control for Teleoperation of Uncertain Robot Manipulator Using Neural Networks
期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 5, 页码: 3282-3292
作者:
Yang, Chenguang
;
Peng, Guangzhu
;
Cheng, Long
;
Na, Jing
;
Li, Zhijun
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  |  
浏览/下载:76/0
  |  
提交时间:2021/05/31
Robot sensing systems
Force
Robot kinematics
Artificial neural networks
Admittance
Torque
Admittance control
error transformation
force observer
Kinect
neural adaptive control
neural networks (NNs)
robot
Fixed-time observer based adaptive neural network time-varying formation tracking control for multi-agent systems via minimal learning parameter approach
期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2020, 卷号: 14, 期号: 9, 页码: 1147-1157
作者:
Xiong, Tianyi
;
Pu, Zhiqiang
;
Yi, Jianqiang
;
Tao, Xinlong
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  |  
浏览/下载:50/0
  |  
提交时间:2020/07/06
neurocontrollers
multi-agent systems
Lyapunov methods
closed loop systems
nonlinear control systems
time-varying systems
adaptive control
observers
uncertain systems
position control
radial basis function networks
robust control
control system synthesis
learning (artificial intelligence)
minimal learning-parameter approach
fixed-time CLSO
time-varying formation tracking problem
formation tracking control scheme
multiagent systems
time-varying formation tracking control problem
model uncertainties
velocity measurements
radial basis function neural networks
fixed-time cascaded leader state observer
fixed-time observer-based adaptive neural network time-varying formation tracking control
RBFNN-based adaptive control scheme
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