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CAS IR Grid
机构
数学与系统科学研究院 [4]
力学研究所 [2]
长春光学精密机械与物... [2]
地质与地球物理研究所 [1]
自动化研究所 [1]
武汉岩土力学研究所 [1]
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OAI收割 [12]
内容类型
期刊论文 [9]
会议论文 [3]
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2023 [1]
2020 [2]
2016 [2]
2015 [1]
2013 [3]
2012 [1]
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学科主题
一般力学 [2]
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The improvement of sparsity gravity inversion using an adaptive lanczos bidiagonalization method
期刊论文
OAI收割
FRONTIERS IN EARTH SCIENCE, 2023, 卷号: 10, 页码: 16
作者:
Meng, Zhaohai
;
Wang, Yanfei
;
Li, Jinhui
;
Li, Fengting
;
Zhang, Zishan
  |  
收藏
  |  
浏览/下载:30/0
  |  
提交时间:2023/03/30
sparsity constraint
gravity inversion
optimization iteration
adaptive lanczos bidiagonalization
projected subspace method
Controller Optimization for Multirate Systems Based on Reinforcement Learning
期刊论文
OAI收割
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 3, 页码: 417-427
作者:
Zhan Li
;
Sheng-Ri Xue
;
Xing-Hu Yu
;
Hui-Jun Gao
  |  
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2021/02/22
Multirate system
reinforcement learning
policy iteration
optimal control
controller optimization.
LOW-RANK MATRIX ITERATION USING POLYNOMIAL-FILTERED SUBSPACE EXTRACTION
期刊论文
OAI收割
SIAM JOURNAL ON SCIENTIFIC COMPUTING, 2020, 卷号: 42, 期号: 3, 页码: A1686-A1713
作者:
Li, Yongfeng
;
Liu, Haoyang
;
Wen, Zaiwen
  |  
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2020/09/23
low-rank matrix iteration
eigenvalue decomposition
inexact optimization method
polynomial filter
subspace extraction
A smoothing SQP framework for a class of composite minimization over polyhedron
期刊论文
OAI收割
MATHEMATICAL PROGRAMMING, 2016, 卷号: 158, 期号: 1-2, 页码: 467-500
作者:
Liu, Ya-Feng
;
Ma, Shiqian
;
Dai, Yu-Hong
;
Zhang, Shuzhong
  |  
收藏
  |  
浏览/下载:47/0
  |  
提交时间:2018/07/30
Composite L-q minimization
epsilon-KKT point
Nonsmooth nonconvex non-Lipschitzian optimization
Optimality condition
Smoothing approximation
Worst-case iteration complexity
Asymptotic Perturbation Bounds for Probabilistic Model Checking with Empirically Determined Probability Parameters
期刊论文
OAI收割
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2016, 卷号: 42, 期号: 7, 页码: 623-639
作者:
Su, Guoxin
;
Feng, Yuan
;
Chen, Taolue
;
Rosenblum, David S.
  |  
收藏
  |  
浏览/下载:33/0
  |  
提交时间:2018/07/30
Asymptotic perturbation bound
discrete-time Markov chain
numerical iteration
optimization
parametric Markov chain
perturbation analysis
probabilistic model checking
quadratic programming
A parallel line searchsubspace correction method for composite convex optimization
期刊论文
OAI收割
journaloftheoperationsresearchsocietyofchina, 2015, 卷号: 3, 期号: 2, 页码: 163
作者:
Dong Qian
;
Liu Xin
;
Wen Zaiwen
;
Yuan Yaxiang
  |  
收藏
  |  
浏览/下载:26/0
  |  
提交时间:2021/01/14
Line search
Block coordinate descent method
Domain decomposition
Jacobian-type iteration
Distributed optimization
Additive block diagonal preconditioning for block two-by-two linear systems of skew-Hamiltonian coefficient matrices
期刊论文
OAI收割
NUMERICAL ALGORITHMS, 2013, 卷号: 62, 期号: 4, 页码: 655-675
作者:
Bai ZZ
;
Chen F(陈芳)
;
Wang ZQ
收藏
  |  
浏览/下载:26/0
  |  
提交时间:2013/05/03
Block two-by-two matrices
PMHSS iteration
Block diagonal matrix
Preconditioning
Spectral properties
PDE-constrained optimization
An Image Reconstruction Algorithm for Electrical Capacitance Tomography Based on Robust Principle Component Analysis
期刊论文
OAI收割
SENSORS, 2013, 卷号: 13, 期号: 2, 页码: 2076-2092
作者:
Lei, Jing
;
Liu, Shi
;
Wang, Xueyao
;
Liu, Qibin
收藏
  |  
浏览/下载:26/0
  |  
提交时间:2015/10/23
electrical capacitance tomography
capacitance sensor
image reconstruction
inverse problem
robust principle component analysis
forward-backward splitting technique
alternating direction iteration optimization method
Preconditioned MHSS iteration methods for a class of block two-by-two linear systems with applications to distributed control problems
期刊论文
OAI收割
IMA JOURNAL OF NUMERICAL ANALYSIS, 2013, 卷号: 33, 期号: 1, 页码: 343-369
作者:
Bai ZZ
;
Benzi M
;
Chen F(陈芳)
;
Wang ZQ
收藏
  |  
浏览/下载:27/0
  |  
提交时间:2013/03/25
block two-by-two matrices
PMHSS iteration
preconditioning
spectral properties
PDE-constrained optimization
KKT systems
Classification of hyperspectral image based on SVM optimized by a new particle swarm optimization (EI CONFERENCE)
会议论文
OAI收割
2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2012, June 1, 2012 - June 3, 2012, Nanjing, China
作者:
Gao X.
;
Yu P.
;
Yu P.
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2013/03/25
Support Vector Machine (SVM) is used to classify hyperspectral remote sensing image in this paper. Radial Basis Function (RBF)
which is most widely used
is chosen as the kernel function of SVM. Selection of kernel function parameter is a pivotal factor which influences the performance of SVM. For this reason
Particle Swarm Optimization (PSO) is provided to get a better result. In order to improve the optimization efficiency of kernel function parameter
firstly larger steps of grid search method is used to find the appropriate rang of parameter. Since the PSO tends to be trapped into local optimal solutions
a weight and mutation particle swam optimization algorithm was proposed
in which the weight dynamically changes with a liner rule and the global best particle mutates per iteration to optimize the parameters of RBF-SVM. At last
a 220-bands hyperspectral remote sensing image of AVIRIS is taken as an experiment
which demonstrates that the method this paper proposed is an effective way to search the SVM parameters and is available in improving the performance of SVM classifiers. 2012 IEEE.