radial basis function networks approach
Numerical solution of Fokker-Planck equation using the integral radial basis function networks
... present approach include (i) to yield a meshless discretisation of FPEs; (ii) to improve the approximation accuracy by avoiding the reduction in convergence rate caused by differentiation; (ii) to reduce the noise ...
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Computing non-Newtonian fluid flow with radial basis function networks
... MQs are employed to compute flows of a power-law fluid through circular and non-circular tubes, while TPSs are used to simulate the flow of a viscoelastic fluid through a square duct. For simplicity, in the MQ-based ...
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A Survey on Data Classification using Machine Learning Techniques
... with radial basis function networks based on a novel kernel density estimation ...learning approach for well-organized construction of the radial basis function ...
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Learning enhancement of radial basis function network with particle swarm optimization
... learning approach for RBF Network (DCRBF), which was a hybrid system consisting of several sub-RBF ...proposed approach had faster learning speed with slightly better generalization ...
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Approximation of function and its derivatives using radial basis function networks
... both function and especially its ...nite basis and all derivatives are obtained as a ...indirect approach the start- ing point is the decomposition of the highest derivatives into some nite ...the ...
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Forecasting US unemployment with radial basis neural networks, kalman filters and support vector regressions
... kernel function transforms the original input space into one with more dimensions, where a linear decision border can be ...cross-validation approach (Cao et ...
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Computation of laminated composite plates using integrated radial basis function networks
... tions (42)–(44) are represented by RBFNs, using either (45)–(47) for the DRBFN approach or (60)–(64) for the IRBFN approach. The system of PDEs is then dis- cretized by means of point collocation. The RBFN ...
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Numerical solution for the fluid flow between active elastic walls
... To solve equation (4) we developed numerical codes based on the one- dimensional Integrated Radial Basis Function Networks (1 d-irbfn ) method. This method was tested in many engineering ...
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Forecasting the geomagnetic activity of the Dst Index using radial basis function networks
... modelling approach, aimed at obtaining efficient models based on limited input- output observational data, provides a powerful tool for analysing and forecasting geomagnetic activities including the prediction of ...
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Snow cover thickness estimation using radial basis function networks
... els for snow parameter estimation. Machine learning meth- ods have been widely used in hydrology and water resources (Gray and Male, 2004; Coulibaly et al., 2001; Agarwal et al., 2006). In particularly when applied to ...
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Logic Programming In Radial Basis Function Neural Networks
... step function within feedforward neural networks (Hölldobler and Kalinke, 1994; Hitzler et ...their approach, because of Funahashi’s theorem (Funahashi, ...continuous function on a compact ...
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Numerical solution of differential equations using multiquadric radial basis function networks
... nite basis and all derivatives are obtained as a ...indirect approach the starting point is the decomposition of the highest derivatives present in the relevant DEs into some nite ...the function ...
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Solving high order ordinary differential equations with radial basis function networks
... a function and its derivatives, the numer- ical example above indicated that the indirect approach performs well for a wide range of ...indirect approach, Gaussian elimination is applied to solve the ...
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Mathematical Modeling with Local Volatility Surface by Radial Basis Function Approach
... used radial basis function method for solving options pricing model in 1999 ...volatility function for options pricing model also in 1999 ...especially radial basis functions ...
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Computation of transient viscous flows using indirect radial basis function networks
... This approach allows a precise representation of the interface whereas its main drawback is the severe deformation of the mesh as the interface ...second approach, which is based on fixed grids, includes ...
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Computation of laminated composite plates using integrated radial basis function networks
... equations (42)–(44) are represented by RBFNs, using either (45)–(47) for the DRBFN approach or (60)–(64) for the IRBFN approach. The sys- tem of PDEs is then discretized by means of point collocation. The ...
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Design of Aperture Coupled Microstrip Antenna Using Radial Basis Function Networks
... using radial basis function (RBF) nets are developed for the design of Aperture Coupled Microstrip Antennas (ACMSA) for different number of design ...network approach elimi- nates the long ...
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Prediction of dementia patients: A comparative approach using parametric vs. non parametric classifiers
... Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification trees and Ran- dom Forests) as compared to Linear Discriminant ...
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Function Approximation Using Robust Radial Basis Function Networks
... this approach but Fogel and Huang [18] proposed a minimal volume recursive algorithm (FHMV) which minimizes the size of an ellip- soid and was attractive for on-line ...
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Radial Basis Function Networks for Conversion of Sound Spectra
... processing approach has been pro- posed by Stylianou et ...conversion function was build from training examples and was used to convert the spectral features of a first speaker in the spectral features of a ...
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