radial basis neural networks
Implementation Of Hybrid Radial Basis Neural Networks For The Classification Of Customers Of An Sme
... deep neural network-based classifier for brain tumor diagnosis”, en Elsevier Science Direct, Applied Soft Computing, Volume 82, September 2019, 105528September 2019, 105528 ...
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Comparison of multilayer and radial basis function neural networks for text dependent speaker recognition
... artificial neural networks to both text-independent and text-dependent speaker recognition ...of radial basis function (RBF) networks ...MLP networks [14, 5, ...RBF ...
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Comparison between Multi Layer Perceptron and Radial Basis Function Networks for Sediment Load Estimation in a Tropical Watershed
... a neural group is provided with data through the input layer, the neurons in this first layer propagate the weighted data and randomly selected bias through the hidden ...
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Prediction of the pharmaceutical solubility in water and organic solvents via different soft computing models
... artificial neural networks, including multilayer perceptron, radial basis function, and support vector machine, were constructed to predict the solubility of these different pharmaceutical ...
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Filtered Wall: An Automated System to Filter Unwanted Messages from OSN User Walls
... of neural learning which is today recognized as one of the most efficient solutions in text ...on Radial Basis Function Networks (RBFN) with Self Organizing Neural Network (SOINN) for ...
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An Approach of Artificial Neural Networks Modeling Based on Fuzzy Regression for Forecasting Purposes
... artificial neural networks, some data mining approaches are often applied in network training process, namely, Dynamic, Multiple, Prune, Exhaustive prune data-mining methods, as well as Networks with ...
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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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Face Recognition Using Neural Networks
... are extracted from the face region. The distance between the eye balls and the distance between the mouth end points are calculated using the distance calculation algorithm. Then the distance values between the left eye ...
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Direction of Arrival and State of Polarization Estimation Using Radial Basis Function Neural Network (Rbfnn)
... Abstract—A Neural Network architecture is applied to the problem of Direction of Arrival (DOA) and state of polarization estimation using a uniform circular cross and tri-crossed-dipoles antenna ...layer ...
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A Computerized Neural Network System to Filter Unwanted Messages from OSN User Walls
... of neural learning which is today recognized as one of the most efficient solutions in text ...on Radial Basis Function Networks (RBFN) with Self Organizing Neural Network (SOINN) for ...
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Real-time face recognition system using radial basis function neural networks
... Low Level Analysis ,..-- Feature-Based r-- Feature Analysis Approach .._ Active Shape Model Face Detection 1-- Linear Subspace r- Image-Based '-- Method Neural Network Approach - Statist[r] ...
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Long-Term Peak Demand Forecasting by Using Radial Basis Function Neural Networks
... to neural networks [1] [2] [4] [8] [10], support vector machines [15], genetic algorithms [14], wavelet networks [12] [13], fuzzy logics [16] and expert system [17] ...
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Numerical Solution of Sixth Order Differential Equations Arising in Astrophysics by Neural Network
... Hopfield neural network ...forward neural network. Artificial neural networks based on Broyden-Fletcher-Goldfarb-Shanno (BF GS) optimization technique for solving ordinary and partial ...
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Combining gene expression programming and genetic algorithm as a powerful hybrid modeling approach for pear rootstocks tissue culture media formulation
... perceptron neural networks (MLPNN) and Multiple Linear Regression (MLR) ...as Radial Basis Function Neural Network (RBFNN) and Gene Expression Programming ...
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Performance Evaluation Analysis of MLP & DG-RBF Feed Forward Neural Networks for Pattern Classification of Handwritten English Curve Scripts Naveen Kumar Sharma 1, S R Pande2 and Manu Pratap Singh 3*
... forward neural network trained with back propagation algorithm does not perform better in comparison to feed forward neural network trained with decent gradient with ...the basis function parameters ...
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Comparative Application of Radial Basis Function and Multilayer Perceptron Neural Networks to Predict Traffic Noise Pollution in Tehran Roads
... the neural network model to pre- dict the noise levels due to continuous and non- continuous traffic flow in ...back-propagation neural network (BPN) and a regression model to predict the noise of ...
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Learning enhancement of radial basis function network with particle swarm optimization
... Radial Basis Function (RBF) Networks form a class of Artificial Neural Networks (ANNs), which has certain advantages over other types of ANNs, such as better approximation capabilities, ...
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Detecting Network Intrusion Using BPA & RBF Neural Network Algorithms
... reliable networks become more critical. The computer networks are facing intelligent attacks has increased drastically in recent ...Propagation Neural Network (BPA) and Radial Basis ...
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Application of Artificial Neural Network and Adaptive Neural based Fuzzy Inference System Techniques in Estimating of Virtual Water
... (MLP), Radial Basis Functions (RBF), and Generalized Regression Neural Networks (GRNN) as well as ANFIS were examined in estimation of VW using measured data of the yield and Crop Water ...
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PREDICTION OF MONTHLY RAINFALL OF MANSA REGION USING ARTIFICIAL NEURAL NETWORK (ANN)
... the Radial Basis Exact Fit, Feed Forward Back propagation, Cascade Forward Back propagation neural networks model for predicting the average monthly rainfall of Mansa ...
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