radial basis functions neural network
Radial Basis Neural Network Based Islanding Detection in Distributed Generation
... proposed neural network structure and methodology for islanding protection is presented ...[26-32]. Radial basis functions neural network has its origins in techniques for ...
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EFFICIENT SCHEDULING OF WORKFLOW IN CLOUD ENVIORNMENT USING BILLING MODEL AWARE TASK CLUSTERING
... 3.1 Radial basis function neural network model The radial basis function neural network (RBFNN)[8] has a feed forward architecture with an input layer, a hidden ...
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Support Vector Machine to predict the discharge coefficient of Sharp crested w-planform weirs
... Perceptron Neural Network (MLPNN), Radial Basis Neural Network (RBFNN) and support vector machine ...kernel functions were ...kernel functions for developing the ...
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Dynamic Threshold Selection for Sequential Learning in Radial Basis Function Networks
... RBF network implementations is ...artificial neural network that is able to observe, on its own, the characteristics of the sequence of input vectors, and how the target output vector of the system ...
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Advanced approach to numerical forecasting using artificial neural networks
... cial neural networks can be used for forecasting and they are able to work with extremely big data sets in reasonable ...uses Radial Basis Functions neural net- work in comparison with ...
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A Survey of Forecasting Preprocessing Techniques using RNs
... Artificial Neural Network (ANN) based on radial basis functions (RBFs) and the prediction results are compared with the ones we get without these preprocessing tools, with the high ...
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A tunable approximately piecewise linear model derived from the modified probabilistic neural network
... The Modified Probabilistic Neural Network structure allows it to model data by weighting piecewise linear models associated with each of the network’s radial basis functions in[r] ...
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Radial basis function neural network learning with modified backpropagation algorithm
... RBFNN is an ANN, which uses RBF as activation functions. RBFNN forms a unique kind of ANN architecture with only three layers. In RBFNN, different layers of the network perform different tasks. This kind of ...
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Radial basis function neural network for software engineering measures A survey
... individual functions at various ...Logic, Neural Network, and Genetic Algorithm ...(Radial Basis Function) and SVM has some secure relationship among them where they both are identified ...
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Face Recognition using Rectangular Feature
... A radial basis function network is an artificial neural network that uses radial basis functions as activation ...of radial basis ...A Radial ...
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Prediction of Salinity Variations in a Tidal Estuary Using Artificial Neural Network and Three Dimensional Hydrodynamic Models
... Salinity is an important indicator of the health of the aquatic ecosystem in tidal estu- aries. In the present study, estuarine salinities were predicted using ANN (BPNN and RBFNN) and three-dimensional hydrodynamic ...
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A Neural Network Method Based on Mittag-Leffler Function for Solving a Class of Fractional Optimal Control Problems
... NCP functions. An approach based on feed-forward neural networks, optimization techniques, and collocation methods is then stated to determine the approximate solution of the ...
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A Radial Basis Function Approach to Retrieve Soil Moisture and Crop Variables from X-Band Scatterometer Observations
... when network was trained with VV-polarization ...regression network, the optimized spread constant was ...the network for the optimized spread constant of ...the network was trained with ...
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Rapid evaluation of radial basis functions
... dial basis function interpolants that can be used for all usual radial ba- sis functions discussed in this and previous ...of radial basis functions, which form the core of our ...
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Detecting Network Intrusion Using BPA & RBF Neural Network Algorithms
... propagation neural network intrusion detection system (BPNNIDS) and the second system was the RBF neural network intrusion detection system which was capable of classifying the attacks into ...
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Application of Meshless Methods for Thermal Analysis
... Similar to FEM techniques, meshless methods produce banded system matrices that can be handled in similar fashion. Both sets of methods can utilize either direct methods based on Gauss elimination or matrix decomposition ...
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On spherical averages of radial basis functions
... and d even, for which we first establish that these are, indeed, polyharmonic radial basis functions. It is usual to refer the reader to standard texts such as Jones [10] for the explicit formulae ...
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Adaptive Inverse Control of Proton Exchange Membrane Fuel Cell Using RBF Neural Network
... If the inverse model of PEMFC system is well-identified, necessary control signal for the system to track the reference voltage will be provided alone via inverse controller and the output of feedback controller will ...
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Benchmarking of the Key Sample Machine
... of basis functions drawn from a set of ...one basis function at a time - the one reduces the cost most - until some chosen criterion stops decreasing, is ...the neural, by gradient descent, ...
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Learning Methods of Radial Basis Function Neural Network
... RBF network design is the design meets the accuracy requirements of the minimum structure of neural network, in order to ensure the generalization ability of the ...
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