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科研机构
中南大学 [7]
兰州理工大学 [2]
青藏高原研究所 [1]
地理科学与资源研究所 [1]
上海大学 [1]
内容类型
期刊论文 [12]
发表日期
2018 [12]
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Adaptive Detection and Preprocessing Method for Abnormal Wind Speed of Wind Farm Based on Deep Boltzmann Machine
期刊论文
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, 2018, 卷号: 33, 页码: 205-212
作者:
Lin, Jie
;
Wu, Butuo
;
Chen, Wei
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2020/11/14
Anomaly detection
Data acquisition
Data handling
Forecasting
Hidden Markov models
Signal processing
Speed
Statistics
Stochastic systems
Wind power
Data acquisition system
Deep boltzmann machines
Empirical Mode Decomposition
Outlier identification
Pre-processing method
Prediction accuracy
Pretreatment methods
Wind speed sequences
Voltage Signal Reconstruction Method of Wind Power Converter Based on ITD and Improved Inner Product Compressed Sensing
期刊论文
Gaodianya Jishu/High Voltage Engineering, 2018, 卷号: 44, 期号: 7, 页码: 2338-2345
作者:
Dong, Weiguang
;
Zhang, Xiaodong
;
Tang, Min'an
;
Guo, Junfeng
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2020/11/14
Compressed sensing
Computational efficiency
Discrete cosine transforms
Power converters
Signal detection
Voltage measurement
Wind power
Generalized orthogonal
High speed transmission
Intrinsic time-scale decompositions
Jaccard coefficients
Operational efficiencies
Reconstruction accuracy
Reconstruction algorithms
Simultaneous operation
Short-term wind speed prediction using an extreme learning machine model with error correction
期刊论文
ENERGY CONVERSION AND MANAGEMENT, 2018, 卷号: 162, 期号: 0, 页码: 239-250
作者:
Li, X (Li, Xin)
;
Wang, LL (Wang, Lili)
;
Bai, YL (Bai, Yulong)
收藏
  |  
浏览/下载:15/0
  |  
提交时间:2019/06/13
Neural-network
Feature-selection
Search Algorithm
Time-series
Decomposition
Elm
Emd
Optimization
System
China
Scale-Specific Controller of Carbon and Water Exchanges Over Wheat Field Identified by Ensemble Empirical Mode Decomposition
期刊论文
INTERNATIONAL JOURNAL OF PLANT PRODUCTION, 2018, 卷号: 12, 期号: 1, 页码: 43-52
作者:
He, Liang
;
Li, Jun
;
Harahap, Mahrita
;
Yu, Qiang
收藏
  |  
浏览/下载:23/0
  |  
提交时间:2019/05/30
Multi-scale
NEE
LE
Environmental factor
Ensemble empirical mode decomposition
Smart deep learning based wind speed prediction model using wavelet packet decomposition, convolutional neural network and convolutional long short term memory network
期刊论文
Energy Conversion and Management, 2018, 卷号: 166, 页码: 120-131
作者:
Liu, Hui*
;
Mi, Xiwei
;
Li, Yanfei
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2019/12/03
Wind speed prediction model
Wavelet packet decomposition
Convolutional neural network
Convolutional long short term memory network
Deep learning
Multi-step wind speed forecasting using EWT decomposition, LSTM principal computing, RELM subordinate computing and IEWT reconstruction
期刊论文
Energy Conversion and Management, 2018, 卷号: 167, 页码: 203-219
作者:
Li, Yanfei
;
Wu, Haiping
;
Liu, Hui*
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/12/03
Wind speed forecasting
Hybrid model
Empirical wavelet transform
Long short term memory network
Regularized extreme learning machine
Inverse empirical wavelet transform
An experimental investigation of three new hybrid wind speed forecasting models using multi-decomposing strategy and ELM algorithm
期刊论文
Renewable Energy, 2018, 卷号: 123, 页码: 694-705
作者:
Liu, Hui
;
Mi, Xiwei
;
Li, Yanfei*
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2019/12/03
Wind speed predictions
Wind speed decomposing performance
Wavelet packet decomposition
Empirical mode decomposition
Extreme learning machine
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
Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM
期刊论文
Energy Conversion and Management, 2018, 卷号: 159, 页码: 54-64
作者:
Liu, Hui*
;
Mi, Xiwei
;
Li, Yanfei
收藏
  |  
浏览/下载:11/0
  |  
提交时间:2019/12/03
Wind speed forecasting
Variational mode decomposition
Singular spectrum analysis
Deep learning
Long short term memory network
Extreme learning machine
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