radial basis function technique
A numerical technique based on integrated RBFs for the system evolution in molecular dynamics
... Radial basis function networks (RBFNs) have emerged as a powerful numerical tool for the solution of differential equations (e.g. Fasshauer, 2007). These approximators are able to work well (i.e. ...
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An Autonomous Incremental Learning Algorithm for Radial Basis Function Networks
... during the initial learning phase. The proposed learning algorithm works in real time if the dimensions of data are not too high. For high-dimensional data (e.g., image data and DNA microarray data), however, the ...
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Computation of transient viscous flows using indirect radial basis function networks
... indirect/integrated radial-basis-function network (IRBFN) method is further developed to solve transient partial dif- ferential equations (PDEs) governing fluid flow ...
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A radial basis function WENO method with stencil adaptivity
... It was observed in the numerical experiments in [1] that polynomial reconstruction schemes may lead to numerical instability. To this end, Aboiyar et al [2] proposed WENO reconstruc- tions over conforming unstructured ...
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Face Recognition by Radial Basis Function Network (RBFN)
... In this paper, an effective method of face recognition technique has been presented. Image processing algorithms based on Radial basis function network has been used in this paper. This paper ...
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Logic Programming In Radial Basis Function Neural Networks
... The first objective of Chapter 5 is to modified the prey predator algorithm to train the RBFNNs. The second objective of Chapter 5 is establish A new method for architecture selection, using to determine the best number ...
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C2-Element radial basis function methods for some continuum mechanics problems
... operator-splitting technique can be ap- plied to factorise a 2D problem into 1D problems in Cartesian directions whose systems are then transformed easily into standard tridiagonal ...
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A stable and accurate control-volume technique based on integrated radial basis function networks for fluid-flow problems
... 6th Australasian Congress on Applied Mechanics 11:20 to 11:40 11:40 to 12:00 Thanapong Chaichana [1250] An investigation of hemodynamic function in realistic coronary arteries: prelimina[r] ...
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Title: Face Recognition Using K-Means and RBFN
... Abstract: This paper presents face recognition errand by using k-means with radial basis function network technique. The facial recognition system has proposed to recognize the faces which are ...
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A hybrid metaheuritic technique developed for hourly load forecasting
... Hybrid technique of PSO with radial basis function (RBF) neural network was applied to load forecasting problem which improved the traditional RBF model [40]; however, the quality of results ...
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Compact integrated radial basis function modelling of particulate suspensions
... (DF) technique, to evaluate the interactive forces between the immersed bound- ary (IB) and the fluid, which is equivalent to applying a forcing term to the Navier-Stokes ...
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Medium term load forecasting using evolutionary programming least square support vector machine
... intelligent-based technique namely Evolutionary Programming- Least-Square Support Vector Machine (EP-LSSVM) to forecast a medium term load ...the Radial Basis Function (RBF) Kernel parameters ...
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Nonlinear Image Restoration Using a Radial Basis Function Network
... blurring function is known and smooth. A cost function is then minimized by using the steepest descent ...blurring function nor the original image is ...blurring function. Since the GRBFN ap- ...
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A RADIAL BASIS FUNCTION PARTITION OF UNITY METHOD FOR TRANSPORT ON THE SPHERE
... In order for the RBF-PUM to be practical, adaptive and static node refinements needs to be developed. Note that with mesh-free methods only the location of the nodes needs to be considered. Starting with the ideas of ...
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Training of Radial Basis Function Using Particle Swarm Optimization
... optimization technique developed by ...i.e Radial Basis Function by ...radius. Radial Basis Function emerged as a variant of artificial neural networks in late ...a ...
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Maximum 2-satisfiability in radial basis function neural network
... the Radial Basis Function Neural Network with Maximum 2-Satisfiability in the aspect of ratio of satisfied clause (RSC), the root mean square error (RMSE), and CPU ...called Radial ...
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FEATURE SELECTION USING MODIFIED ANT COLONY OPTIMIZATION APPROACH (FS MACO) BASED FIVE LAYERED ARTIFICIAL NEURAL NETWORK FOR CROSS DOMAIN OPINION MINING
... learning technique named Support Vector Machine (SVM) using Radial-basis kernel function (RBF) and a Particle Swarm Optimization algorithm to optimize the parameters of SVM for effective ...
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Local moving least square-one-dimensional integrated radial basis function networks technique for incompressible viscous flows
... stream function and ...shape function possesses the Kronecker- δ property which allows an exact imposition of the essential boundary ...1D-IRBFN technique are more accurate than the one using the ...
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Adaptive Radial Basis Function Detector for Beamforming
... +1 , [ y Lin ( k )] ≥ 0 , −1 , [ y Lin ( k )] < 0 , (3) where θ = [θ 1 · · · θ L ] T denotes the complex-valued linear beamformer’s weight vector and [•] the real part. Classically, the L-MMSE solution for the weight ...
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Radial Basis Function Assisted Turbo Equalization
... a radial basis function (RBF)-assisted equalizer as the soft-in/soft-out (SISO) equal- izer in the context of ...complexity-reduction technique for the RBF TEQ, and in Section VII, we conclude ...
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