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pro vyhledávání: '"Hierarchical RBF"'
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Publikováno v:
IEEE Transactions on Industrial Informatics. 14:931-940
Radial basis function (RBF) networks, because of their universal approximation ability, have been widely applied to industrial process modeling. In this study, an Improved ErrCor (IErrCor) algorithm—an extension of error correction (ErrCor) algorit
Publikováno v:
Applied Numerical Mathematics. 116:157-171
Representation of curves and surfaces is a basic topic in computer graphic and computer aided design (CAD). In this paper we focus on theoretical and practical issues in using radial basis functions (RBF) for reconstructing implicit curves and surfac
Publikováno v:
Jurnal Ilmu Komputer dan Informasi, Vol 10, Iss 1, Pp 36-42 (2017)
SVM (Support Vector Machine) with RBF (Radial Basis Function) kernel is a frequently used classification method because usually it provides an accurate results. The focus about most SVM optimization research is the optimization of the the input data,
Autor:
Scott A. Sarra, Samuel Cogar
Publikováno v:
Engineering Analysis with Boundary Elements. 75:36-45
Radial Basis Function (RBF) methods are important tools for scattered data interpolation and for the solution of PDEs in complexly shaped domains. Several approaches for the evaluation of RBF methods are known. To date, the most noteworthy methods ar
Autor:
Hossein Mirinejad, Tamer Inanc
Publikováno v:
Robotics and Autonomous Systems. 87:219-225
A direct solution to optimal control problems is introduced based on interpolating global radial basis functions (RBFs) on arbitrary collocation points. In the proposed approach, called the RBF collocation method, states and controls are parameterize
Publikováno v:
Applied Soft Computing. 49:485-497
Display Omitted We present a new cooperative learning method for RBF networks based on PSO.The method allows for variable-width basis functions, increasing model flexibility.A compact representation scheme is introduced using two distinct cooperative
Publikováno v:
Neural Computing and Applications. 29:1445-1454
An adaptive p-step prediction model for nonlinear dynamic processes is developed in this paper and implemented with a radial basis function (RBF) network. The model can predict output for multi-step-ahead with no need for the unknown future process o
Publikováno v:
Computers & Mathematics with Applications. 72:1096-1117
This paper proposes a high-order finite volume method based on radial basis function (RBF) reconstruction for the solution of Euler and Navier-Stokes equations on unstructured grids. Unlike traditional polynomial K-exact method, RBF method has strong
Publikováno v:
Neurocomputing. 199:31-39
A radial basis function (RBF) neural network approach with a fusion of multiple signal candidates in precision motion control is studied in this paper. Sensor weightages are assigned to sensor measurements according to the selector attributes and app