The paper assesses the capabilities of radial basis function mesh deformation for both two and three-dimensional problems. Furthermore, the effectiveness of the deformation technique is assessed for both local, non-smooth deformations and global, smooth deformations. The convergence history of the multi...
The paper presents a new approach for classification and location of faults on a transmission line using a newer version of radial basis function neural network (RBFNN) which provides a more efficient approach for training and computation. The input data to the RBFNN comprise the normalised peak ...
摘要: Training algorithms for radial basis function Kernel classifiers (RBFKCs), such as the canonical support vector machine (SVM), often produce computationally burdensome classifiers when large training data sets are used. Additionally, this complexity is no...
An efficient mesh-deformation algorithm has been developed within an unstructured-grid computational-fluid-dynamics solver framework based on a radial-basis-function volume-interpolation method. The data-transfer problem between fluid and structural solvers is simplified here using a beam structural represent...
In this paper, an improved method for object tracking is proposed using Radial Basis Function Neural Networks. Optimized k-means color segmentation is employed for detecting an object in first frame. Next the pixel-based color features (R, G, B) from object is used for representing object colo...
stepwise regressionRadial Basis Function networksParticle Swarm OptimizationThe objective of this paper is to stress that the size of a Linear Fractional ... G Hardier,C Roos,C Seren - 《Ifac Proceedings Volumes》 被引量: 0发表: 2013年 On the Role of Sparse and Redundant Representations in Im...
Radial Basis Functioon vs Sigmoid Units RBF: RBF units的means 和 widths是通过无监督聚类方法确定的。 一个RBF只能覆盖一个小的局部区域,这使得学习速度很快。通常RBF在上层网络(低维)更合适,sigmoids在下层网络(高维)更合适。 Convergence of Gradient Descent ...
This paper introduces the digital image technology Radial Basis Function (RBF)-Neural network, based on extracting the Steel Ball surface defect image ... YL Zhao,FL Wu,P Wang,... - 《Applied Mechanics & Materials》 被引量: 3发表: 2014年 Classification of Stainless Steel Strips Using Artific...
For instance, based on the Radial Basis Function (RBF) neural network and Surrogate-Based Recurrent Framework (SBRF) [19], Kou et al. [23] proposed a new ROM to predict the dynamic linear behavior under the assumption of small perturbations. In order to capture both linear and nonlinear ...
By combining multilayer perceptrons (MLPs) and radial basis function neural networks (RBF-NNs), an efficient multilayer RBF network is proposed in this work for regression problems. As an extension to the existing multilayer RBF network (RBF-MLP-I), the new multilayer RBF network (RBF-MLP-II)...