Radial basis function
Soft Sensor Based on Dynamic Principal Component Analysis and Radial Basis Function Neural Network for Distillation Column
... Principal component analysis (PCA) is a reliable and simple statistical technique for handling high dimensional, noisy, and correlated measurement data by projecting the data onto a lower dimensional subspace which ...
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Design of Radial Basis Function Neural Networks for Software Effort Estimation
... a radial basis function, which is in general a Gaussian function, and an output layer which builds a linear weighted sum of hidden neuron outputs and supplies the response of the network ...
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Prediction of Reagents Needs Using Radial Basis Function in Teaching Hospital
... Abstract—A robust reagents prediction is able to support the service improvement in laboratories. In this paper, Radial Basis Function Networks (RBFN) method with (3, Q, 1) architecture is used to ...
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Vulnerability Assessment of Power System Using Radial Basis Function Neural Network and a New Feature Extraction Method
... of Radial Basis Function Neural Network (RBFNN) for vulnerability assessment of power system incorporating a new proposed feature extraction method named as the Neural Network Weight Extraction ...
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Performance-oriented asymptotic tracking control of hydraulic systems with radial basis function network disturbance observer
... In this article, using ideas from NNs and ARC approaches for reference, a novel adaptive robust con- troller based on radial basis function (RBF) NNs is pro- posed for a hydraulic actuator. In this ...
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Clinics vol.65 número12
... and radial basis function neural network were significantly larger than those for all individual Orbscan II attributes evaluated ...and radial basis function neural network, ...
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Ore reserve estimation using radial basis functions
... for radial basis function interpolation is related to choosing an adequate kernel or basis ...for basis functions we have to choose one, which could give unbiased ...
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Research on Spatial Estimation of Soil Property Based on Improved RBF Neural Network
... of Radial Basis Function (RBF) Neural Network and improve the accuracy of this method on estimation of soil property space, this study utilizes genetic algorithm to optimize three network parameters ...
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Radial basis functions collocation method for solution of MagnetohydrodynamicNono boundary-layer flows
... In this paper, axisymmetric flows over stretching surfaces in a porous medium in the presence of a magnetic field with the navier boundary condition have been considered. The governing partial differential equation (PDE) ...
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Lat. Am. j. solids struct. vol.14 número7
... The radial basis function (RBF) also referred to as Kansa method (Kansa, 1990a; Kansa, 1990b), as another meshless method, presents itself with some appealing characteris- tics ...shape ...
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Computational complexity evaluation of ann algorithms for image steganalysis
... Abstract - The major growth of information technology is based on the way how the security measures are implemented. Steganography is a technique that implements high level security by hiding a message in a multimedia ...
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J. Braz. Chem. Soc. vol.21 número9
... often complex and time-consuming and can be done only for already synthesized compounds. For this reason, a number of computational methods for the prediction of this parameter have been proposed. In this work, a QSPR ...
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Artificial neural networks: A novel approach to analysing the nutritional ecology of a blowfly species, Chrysomya megacephala
... (MLP), Radial Basis Function (RBF), and Adaptive Neural Network-Based Fuzzy Inference System (ANFIS), to ascertain whether these tools would be able to outperform a classical statistical method ...
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Pesqui. Oper. vol.29 número2
... the basis of many physical phenomena, and its use has also spread into economics, financial forecasting and other fields, including Black and Scholes ...the Radial Basis Function Method, RBF, ...
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J. Braz. Comp. Soc. vol.12 número4
... valued radial basis function (RBF) neural network with phase transmittance (PTRBFNN) outperforms the classical complex valued RBF neural network (RBFNN) for those channels which impose drastic phase ...
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Bol. Ciênc. Geod. vol.23 número1
... the basis of the results, the new parameters (AM) attained a maximum horizontal position error of ...(BPNN), radial basis function neural network (RBFNN) and generalized regression neural ...
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Neural networks based predictive control for thermal comfort and energy savings in public buildings
... by radial basis function neural networks identified by means of a multi-objective genetic algorithm; the cost function that will be optimised to minimise energy consumption and maintain thermal ...
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Comitês de baseados nas Redes SOM e Fuzzy ART com sintonia de parâmetros e seleção de atributos via metaheurísticas evolucionárias
... Classificadores neurais são tipicamente obtidos a partir de técnicas de aprendizagem supervisionada, tais como redes MLP (Multi-Layer Perceptron) e RBF (Radial Basis Function ) (HAYKIN, 2[r] ...
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Mat. Res. vol.17 número6
... the radial distribution of coordination and number density for Cr- and Nb- centered clusters (the radial direction is measured from the origin of the RMC simulation box and is the vertical axis in units of ...
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Singular value decomposition of the radial distribution function for hard sphere and square well potentials.
... Since the Fourier transform of g(r) results in the experimentally measurable structure factor, prediction of the RDF is one of the core goals of liquid state theories. This work was motivated by the lack of an accurate ...
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