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科研机构
华南理工大学 [4]
山东大学 [3]
武汉理工大学 [3]
北京大学 [2]
西安交通大学 [2]
金属研究所 [2]
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内容类型
期刊论文 [21]
会议论文 [6]
其他 [1]
发表日期
2015 [28]
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Generalization Performance of Radial Basis Function Networks
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 卷号: 26, 期号: 3, 页码: 551-564
作者:
Lei, Yunwen
;
Ding, Lixin
;
Zhang, Wensheng
收藏
  |  
浏览/下载:28/0
  |  
提交时间:2015/11/08
Learning theory
local Rademacher complexity
radial basis function (RBF) networks
structural risk minimization (SRM)
Wearable Biometric Authentication Based on Human Body Communication
会议论文
Body Sensor Networks Conference 2015 (bsn 2015), MIT, Cambridge, USA
作者:
Zedong Nie
;
Yuhang Liu
;
Changjiang Duan
;
Zhongzhou Ruan
;
Jingzhen Li
收藏
  |  
浏览/下载:21/0
  |  
提交时间:2016/01/27
Solar panels defect detection based on radial basis function neural network
期刊论文
Faguang Xuebao/Chinese Journal of Luminescence, 2015, 卷号: 36, 期号: 1, 页码: 99-105
作者:
Shen, L.-Y.
;
M. Zhu and X.-Y. Chen
收藏
  |  
浏览/下载:11/0
  |  
提交时间:2016/08/24
Evolving RBF neural networks for rainfall prediction using hybrid particle swarm optimization and genetic algorithm
期刊论文
Neurocomputing, 2015, 卷号: 148, 页码: 136-142
作者:
Wu, Jiansheng*
;
Long, Jin
;
Liu, Mingzhe
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2019/12/04
Particle swarm optimization
Genetic algorithm
Radial basis function neural network
Rainfall prediction
Ship Traffic Volume Forecast in Bridge Area Based on Enhanced Hybrid Radial Basis Function Neural Networks
会议论文
3rd International Conference on Transportation Information Safety, Wuhan, PEOPLES R CHINA, JUN 25-28, 2015
作者:
Yang, Liang*
;
Liu, Qing(刘清)
;
Hao, Yong
;
Zhu, Xiangyu
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2019/12/04
waterway transportation
vessel traffic volume
RBF neural network
regression tree
particle swarm optimization(PSO)
forecast
A Stock Market Forecasting Model Combining Two-Directional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Network
期刊论文
PLOS ONE, 2015, 卷号: 10, 期号: 4, 页码: e0122385
作者:
Guo, Zhiqiang*
;
Wang, Huaiqing
;
Yang, Jie
;
Miller, David J.
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/12/04
Forecasting,Stock markets,Principal component analysis,Neural networks,Curve fitting,Algorithms,Eigenvectors,Preprocessing
A self-organizing neural network for PCI failure prediction
会议论文
作者:
Wei, Xinyu
;
Wan, Jiashuang
;
Zhao, Fuyu
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2019/12/02
Failure prediction
Mutual informations
Network complexity
Pellet Cladding Interaction (PCI)
Prediction accuracy
Radial basis function neural networks
RBF Neural Network
Self-organizing neural network
Universal consistency of extreme learning machine for RBFNs case
期刊论文
NEUROCOMPUTING, 2015, 卷号: 168, 期号: [db:dc_citation_issue], 页码: 1132-1137
作者:
Liu, Xia
;
Wan, Anhua
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2019/12/02
Universal consistency
Radial basis function networks
Extreme learning machine
Comparison of four Adaboost algorithm based artificial neural networks in wind speed predictions
期刊论文
Energy Conversion and Management, 2015, 卷号: 92, 页码: 67-81
作者:
Liu, Hui*
;
Tian, Hong-Qi
;
Li, Yan-Fei
;
Zhang, Lei
收藏
  |  
浏览/下载:21/0
  |  
提交时间:2019/12/03
AA
Apriori Algorithm
RBF
Radial Basis Functions
SVR
Support Vector Regression
WDF
Weibull Distribution Function
MSM
Markov Switching Model
BI
Bayesian Interface
PM
Persistent Model
AR
Auto Regressive
ANN
artificial neural networks
BSBM
Bayesian Structural Break Model
KRRM
Kernel Ridge Regression Method
ALS
Active Learning Strategies
SAA
Seasonal Adjustment Algorithm
ESM
Exponential Smoothing Method
MLP
Multilayer Perceptron
BP
Back Propagation
KSF
Kalman Short-term Filtering
NWP
Numerical Weather Prediction
GA
Genetic Algorithm
PSO
Particle Swarm Optimization
PCA
Principal Component Analysis
FAC
First-order Adaptive Coefficient
SAC
Second-order Adaptive Coefficient
BT
Bayesian Theory
SBM
Structural Break Modeling
UKF
Unscented Kalman Filter
OFM
Organizing Feature Maps
EMD
Empirical Mode Decomposition
WT
Wavelet Transform
SVM
Support Vector Machine
ARIMA
Auto Regressive Integrated Moving Average
MAS
Multiple Architecture System
MLR
Multiple Linear Regression
Adaboost
Adaptive Boosting
GD-ALR-BP
Gradient Descent with Adaptive Learning Rate Back Propagation
GDM-ALR-BP
Gradient Descent with Momentum and Adaptive Learning Rate Back Propagation
CG-BP-FR
Conjugate Gradient Back Propagation with Fletcher-Reeves Updates
BFGS
Broyden–Fletcher–Goldfarb–Shanno
Wind energy
Wind speed forecasting
Wind speed predictions
Adaboost algorithm
Neural networks
Wind speed forecasting approach using secondary decomposition algorithm and Elman neural networks
期刊论文
Applied Energy, 2015, 卷号: 157, 页码: 183-194
作者:
Liu, Hui*
;
Tian, Hong-Qi
;
Liang, Xi-Feng
;
Li, Yan-Fei
收藏
  |  
浏览/下载:25/0
  |  
提交时间:2019/12/03
ARIMA
Auto Regressive Integrated Moving Average
ANN
Artificial Neural Networks
KF
Kalman Filter
MSM
Markov Switching Model
PCA
Principal Component Analysis
AA
Apriori Algorithm
BT
Bayesian Theory
SBM
Structural Break Modeling
GMCM
Gaussian Mixture Copula Model
NWP
Numerical Weather Prediction
KSF
Kalman Short-term Filtering
HIRLAM
High Resolution Limited Area Model
BP
Back Propagation
RBF
Radial Basis Function
ALE
Adaptive Linear Element
MAS
Multiple Architecture System
MLR
Multiple Linear Regression
MLP
Multi-Layer Perceptron
RBF
Radial Basis Function
SVM
Support Vector Machine
ABA
Ada-boost Algorithm
PSO
Particle Swarm Optimization
FAC
First-order Adaptive Coefficient
SAC
Second-order Adaptive Coefficient
SAA
Seasonal Adjustment Algorithm
ESM
Exponential Smoothing Method
MFNN
Multi-layer Feed-forward Neural Networks
FRR
Fuzzy Rough Regression
ELM
Extreme Learning Machines
MM5
Fifth Generation Mesoscale Model
GNWP
Global Numerical Weather Prediction
EPA
Evolutionary Programming Algorithm
OFM
Organizing Feature Maps
WD
Wavelet Decomposition
WPD
Wavelet Packet Decomposition
NF
Neuro-Fuzzy
ANFIS
Adaptive Neuro-Fuzzy Inference Systems
PM
Persistent Model
UKF
Unscented Kalman Filter
SVR
Support Vector Regression
FEEMD
Fast Ensemble Empirical Mode Decomposition
HM
Hammerstein Model
AR
Auto Regressive
EMD
Empirical Mode Decomposition
SDA
Secondary Decomposition Algorithm
PRWM
Persistent Random Walk Model
IMFs
Intrinsic Mode Functions
EEMD
Ensemble Empirical Mode Decomposition
GD-BP
Gradient Descent Back Propagation
GDM-BP
Gradient Descent with Momentum Back Propagation
GD-ALR-BP
Gradient Descent with Adaptive Learning Rate Back Propagation
GDM-ALR-BP
Gradient Descent with Momentum and Adaptive Learning Rate Back Propagation
CG-BP-FRU
Conjugate Gradient Back Propagation with Fletcher-Reeves Updates
CG-BP-PR
Conjugate Gradient Back Propagation with Polak-Ribiére Update
CG-BP-PBR
Conjugate Gradient Back Propagation with Powell-Beale Restarts
SCG-BP
Scaled Conjugate Gradient Back Propagation
BFGS-BP
Broyden-Fletcher-Goldfarb-Shanno Back Propagation
OSS-BP
One Step Secant Back Propagation
LM-BP
Levenberg Marquardt Back Propagation
MAE
Mean Absolute Error
MAPE
Mean Absolute Percentage Error
RMSE
Root Mean Square Error
Wind speed forecasting
Secondary decomposition algorithm
Wavelet packet decomposition
Fast ensemble empirical mode decomposition
Elman neural networks
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