RBF Neural Networks
Application of Fuzzy and RBF Neural Networks in the Prediction of Distribution of Coal Seams
... and RBF neural networks were proposed to determine the distribution of coal seam ...by RBF neural network with trained set of ...
5
An Anomaly-Based Method for DDoS Attacks Detection using RBF Neural Networks
... Keywords: DDoS attack; abnormal traffic; RBF neural networks; network security. 1. Introduction As the Internet becomes an essential part of human life, providing security of data passed over the ...
5
The Automatic Model Selection and Variable Width RBF Neural Networks for Chaotic Time Series Prediction
... Keywords: Radial basis function network, Chaotic time series, variable width. Abstract. This paper investigates the construction of radial basis function(RBF) neural networks, and a new self-adaptive ...
7
Date Fruits Classification using MLP and RBF Neural Networks
... Training RBF neural network consists of determining the location of centers and widths for the hidden layer and the weights of the output ...an RBF neural network, and they are discussed in ...
6
Automated Stellar Classification for Large Surveys with EKF and RBF Neural Networks
... an RBF network is very important for raising the ...of RBF hidden neurons, the RBF network as a final classifier performs differently in the classification of ...structure RBF network to ...
8
Concurrent blind channel equalization with phase transmittance RBF neural networks
... (RBF) neural network (NN) with phase transmittance between the input nodes and output, which makes it suitable for channel equalization on quadrature digital modulation ...
8
Bus Arrival Time Prediction Using RBF Neural Networks Adjusted by Online Data
... Function Neural Networks (RBFNN) model is used to learn and approximate the nonlinear relationship in historical data in the first ...BP Neural Networks and RBFNN without online adjustment are ...
9
Adaptive Control OF Nonlinear Multivariable Dynamical Systems Using MRAN-RBF Neural Networks
... (RBF) neural network with Minimal Resource Allocation Network (MRAN) training algorithm were used for off-line stable identification and implements a stable model following adaptive controller by utilizing ...
9
Predictive Subset Selection using Regression Trees and RBF Neural Networks Hybridized with the Genetic Algorithm
... hybrid RBF model, RBF-NN combined with re- gression trees using ridge regression ...hybrid RBF-NN. On the other hand, model selection performance of hybrid RBF-NN model is much more superior ...
20
Prediction of water formation temperature in natural gas dehydrators using radial basis function (RBF) neural networks
... (35 data points) of data were used for validation and testing of models. For MLP model the back propagation algorithm was used to optimize the values of weights and biases. As it mentioned before, a MLP network could ...
8
RBF and SVM Neural Networks for Power Quality Disturbances Analysis
... results of different power quality disturbances. SVM and RBF neural networks are considered as appropriate classifiers for power quality issues, however SVM networks show better performance. ...
8
Model Selection of RBF Networks via Genetic Algorithms
... artificial neural networks is the difficulty of adequately defining values for their free ...(RBF) neural networks can have their free parameters de- fined by Genetic Algorithms ...
144
Short-Term Solar Power Prediction Using an RBF Neural Network
... C. RBF Neural Networks RBF neural networks are a class of feed-forward ANNs constructed based on the function approximation ...an RBF neural ...the RBF ...
9
Genetic algorithm-based RBF neural network load forecasting model
... Function neural network (RBF) as an important branch of neural network, has the best approximation and the best overall ...the RBF neural networks in nonlinear time series ...
6
A Novel Kernel for RBF Based Neural Networks
... conventional RBF uses basis functions which rely on distance measures such as Gaussian kernel of Euclidean distance (ED) between feature vector and neuron’s center, and so ...novel RBF artificial ...
11
Image Segmentation and Edge Detection Using a Neural Networks RBF Approach
... ISSN: 2278 – 1323 All Rights Reserved © 2014 IJARCET 1331 imprecise data, whereas neural networks are endowed with various advantages such as parallelism, learning ability and speed of processing. Both ...
6
Interpretable machine learning: Convolutional neural networks with RBF fuzzy logic classification rules
... biomedical, high-value manufacturing etc.). For example, one could use FL theory to provide linguistic interpretation to classification tasks performed by deep learning networks. There are existing attempts in the ...
8
2 Optimal tracking control based on adaptive rbf neural network (Tc-rbf)
... (RBF) Neural Network, Adaptive Scheme, Disturbance Estimation, Tracking Control, Nonlinear System, Liquid Level Systtem, Active Magnetic Bearing ...artificial neural network and fuzzy logic ...
10
The Modeling and Comparison of GMDH and RBF Artificial Neural Networks in Forecasting Consumption of Petroleum Products in the Agricultural Sector
... the neural networks model the application of which was introduced into macroeconomics in the ...artificial neural networks are deemed to be powerful tools to analyze and model nonlinear ...
15
The Training and Application of RBF Neural Network Based on GWO
... optimizer, Neural network, Approximation, Chaotic ...of RBF neural network, Grey Wolf Optimizer (GWO) and its several variants have been ...the RBF neural network based on GWO is named ...
8