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期刊论文 [48]
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Study on the Sensitive Factors of Structural Nonlinear Damage Based on the Innovation Series
期刊论文
INTERNATIONAL JOURNAL OF STRUCTURAL STABILITY AND DYNAMICS, 2020, 卷号: 20, 期号: 10, 页码: 35
作者:
Chen, Liujie
;
Mei, Yahui
;
Fu, Jiyang
;
Ng, Ching Tai
;
Cui, Zhen
收藏
  |  
浏览/下载:14/0
  |  
提交时间:2021/05/25
Nonlinear damage identification
nonlinear damage-sensitive factor
innovation series
auto-regressive conditional heteroscedasticity
Bearing Degradation Evaluation Using Improved Cross Recurrence Quantification Analysis and Nonlinear Auto-Regressive Neural Network
期刊论文
IEEE ACCESS, 2019, 卷号: 7, 页码: 38937-38946
作者:
Wang, Pu
;
Wang, Hui
;
Yan, Ruqiang
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2019/11/19
cross recurrence quantitative analysis
bearing fault prognosis
nonlinear auto-regressive neural network
Condition-based maintenance
Global Auto-Regressive Depth Recovery via Iterative Non-Local Filtering
期刊论文
IEEE TRANSACTIONS ON BROADCASTING, 2019, 卷号: 65, 页码: 123-137
作者:
Yang, Jingyu
;
Ye, Xinchen
;
Frossard, Pascal
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/12/02
Depth recovery
multi-view depth video
auto-regressive model
nonlocal correlation
iterative filtering
Short-term wind speed forecasting using STLSSVM hybrid model
会议论文
2018 International Conference on Power System Technology, POWERCON 2018 - Proceedings, 2018-11-06
作者:
Yuan, D.
;
Qian, Z.
;
Jing, B.
;
Pei, Y.
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2019/12/30
Backpropagation
Forecasting
Least squares approximations
Particle swarm optimization (PSO)
Speed
Support vector machines
Wind power
Auto-regressive integrated moving average
EEMD
Ensemble empirical mode decompositions (EEMD)
Hybrid methodologies
Least squares support vector machines
Short-term wind speed forecasting
State transitions
Wind speed forecasting
Wind
Spatial autoregressive model for compositional data [成分数据的空间自回归模型]
期刊论文
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics, 2019, 卷号: 45, 页码: 93-98
作者:
Huang, T.
;
Wang, H.
;
Saporta, G.
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/12/30
Intelligent systems
Maximum likelihood estimation
Monte Carlo methods
Auto regressive models
Compositional data
Compositional linear models
Estimation methods
Isometric logratio (ilr) transformation
Numerical data
Parameter estimators
Spatial dependence
Metadata
The Detection of Freezing of Gait in Parkinson's Disease Using Asymmetric Basis Function TV-ARMA Time-Frequency Spectral Estimation Method
期刊论文
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2019, 卷号: 27, 页码: 2077-2086
作者:
Guo, Yuzhu
;
Wang, Lipeng
;
Li, Yang
;
Guo, Lingzhong
;
Meng, Fangang
收藏
  |  
浏览/下载:16/0
  |  
提交时间:2019/12/30
Freezing of gait (FOG)
freeze index (FI)
time-frequency spectral estimation (TFSE)
time-varying auto-regressive moving average (TV-ARMA) model
asymmetric basis function
wearable inertial sensor
Hybrid SVM and ARIMA Model for failure time series prediction based on EEMD
期刊论文
International Journal of Performability Engineering, 2019, 卷号: 15, 页码: 1161-1170
作者:
Sun, Haiyan
;
Wu, Jing
;
Wu, Ji
;
Yang, Haiyan
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2019/12/30
Data handling
Linear regression
Support vector machines
Time series
Auto-regressive integrated moving average
Ensemble empirical mode decomposition
Failure time
Hybrid model
Support vector machines regression
Forecasting
Hybrid quantile regression estimation for time series models with conditional heteroscedasticity
期刊论文
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2018, 卷号: 80, 期号: 5, 页码: 975-993
作者:
Zheng, Yao
;
Zhu, Qianqian
;
Li, Guodong
;
Xiao, Zhijie
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2019/08/22
Bootstrap method
Conditional quantile
Generalized auto-regressive conditional heteroscedasticity
Non-linear time series
Quantile regression
Big multi-step wind speed forecasting model based on secondary decomposition, ensemble method and error correction algorithm
期刊论文
Energy Conversion and Management, 2018, 卷号: 156, 页码: 525-541
作者:
Liu, Hui
;
Duan, Zhu
;
Han, Feng-ze
;
Li, Yan-fei*
收藏
  |  
浏览/下载:38/0
  |  
提交时间:2019/12/03
NWP
numerical weather prediction
CS
Cuckoo search
FS
fuzzy system
WRF
weather research and forecasting
KF
Kalman filter
ARIMA
auto-regressive integrated moving average
ARCH
autoregressive conditional heteroskedasticity
ANN
artificial neural networks
SVM
support vector machine
CRO
Coral Reefs optimization algorithm
ELM
extreme learning machine
MFNN
multi-layer feed-forward neural network
SPSA
simultaneous perturbation stochastic approximation
HM
Hammerstein Model
AR
auto-regressive
AdaBoost
adaptive boosting
MLP
multilayer perceptron
DNN-MRT
deep neural network based meta regression and transfer learning
WD
wavelet decomposition
FEEMD
fast ensemble empirical mode decomposition
EMD
empirical mode decomposition
WPD
wavelet packet decomposition
SSA
singular spectrum analysis
BFGS
Broyden–Fletcher–Goldfarb–Shanno Quasi-Newton Back Propagation
LSSVM
least square support vector machine
PSOGSA
partial swarm optimization combined with gravitational search algorithm
FCM
fuzzy C-means
EEMD
ensemble empirical mode decomposition
SampEn
sample entropy
VMD
variational mode decomposition
MAdaBoost
Modified AdaBoost.RT
WF
wavelet filter
MAE
mean absolute error
MAPE
mean absolute percentage error
RMSE
root mean squared error
CWT
continuous wavelet transform
DWT
discrete wavelet transform
LMD
local mean decomposition
ADMM
alternate direction method of multipliers
Big multi-step wind speed forecasting
Wavelet decomposition
Variational mode decomposition
Sample entropy
Modified adaBoost.RT
Wavelet filter
Comparison of two new intelligent wind speed forecasting approaches based on Wavelet Packet Decomposition, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Artificial Neural Networks
期刊论文
Energy Conversion and Management, 2018, 卷号: 155, 页码: 188-200
作者:
Liu, Hui
;
Mi, Xiwei
;
Li, Yanfei*
收藏
  |  
浏览/下载:41/0
  |  
提交时间:2019/12/03
Wind speed forecasting
Wavelet packet decomposition
Complete Ensemble Empirical Mode Decomposition with Adaptive Noise
Artificial Neural Network
ANN
Artificial Neural Network
AR
Auto Regressive
ARIMA
Auto Regressive Integrated Moving Average
BA
Bat Algorithm
BP
Back-propagation Neural Network
CEEMDAN
Complete Ensemble Empirical Mode Decomposition
CG
Conjugate Gradient
CLSFPA
Flower Pollination Algorithm with Chaotic Local Search
CNN
Convolutional Neural Network
CS
Compressive Sensing
CSA
Cuckoo Search Algorithm
EEMD
Ensemble Empirical Mode Decomposition
ESM
Exponential Smoothing Method
FA
Firefly Algorithm
FAC
First-order Adaptive Coefficient
GA
Genetic Algorithm
GRNN
General Regression Neural Network
HBSA
Hybrid Backtracking Search Algorithm
HWM
Holt-Winters Model
IMFs
Intrinsic Mode Functions
IS
Input parameter Selection
KF
Kalman filter
LSSVM
Least Square Support Vector Machine
MAE
Mean Absolute Error
MAPE
Mean Absolute Percentage Error
MLP
Multilayer Perceptron Neural Network
MOBA
Multi Objective Bat Algorithm
NNCT
No Negative Constraint Theory
NSGA
Non-dominated Sorting Genetic Algorithm
OVMD
Optimized Variational Mode Decomposition
PSO
Particle Swam Optimization
PSOSA
Particle Swarm Optimization based on Simulated Annealing
PSR
Phase Space Reconstruction
RBF
Radial Basis Function Neural Network
RMSE
Root Mean Square Error
SAC
Second-order Adaptive Coefficient
SAM
Seasonal Adjustment Method
SDA
Secondary Decomposition Algorithm
SEA
Seasonal Exponential Adjustment
SOM
Self-Organizing feature Maps
SSA
Singular Spectrum Analysis
SVR
Support Vector Regression
VMD
Variational Mode Decomposition
v-SVM
v-Support Vector Machine
WD
Wavelet Decomposition
WPD
Wavelet Packet Decomposition
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