Results 201 to 210 of about 13,903 (231)
Some of the next articles are maybe not open access.
A novel Hybrid RBF Neural Networks model as a forecaster
Statistics and Computing, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Oguz Akbilgic +2 more
openaire +2 more sources
RBF Neural Networks and Radial Fuzzy Systems
2015RBF neural networks are an efficient tool for acquisition and representation of functional relations reflected in empirical data. The interpretation of acquired knowledge is, however, generally difficult because the knowledge is encoded into values of the parameters of the network.
openaire +2 more sources
A Hybrid Forward Algorithm for RBF Neural Network Construction
IEEE Transactions on Neural Networks, 2006This paper proposes a novel hybrid forward algorithm (HFA) for the construction of radial basis function (RBF) neural networks with tunable nodes. The main objective is to efficiently and effectively produce a parsimonious RBF neural network that generalizes well.
Peng, Jian Xun, Li, Kang, Huang, D.S.
openaire +3 more sources
An ART2/RBF Hybrid Neural Networks Research
2005The radial basis function (RBF) neural networks have been widely used for approximation and learning due to its structural simplicity. However, there exist two difficulties in using traditional RBF networks: How to select the optimal number of intermediate layer nodes and centers of these nodes?
Xuhua Yang 0001 +4 more
openaire +1 more source
RBF Neural Networks and Descartes’ Rule of Signs
2002We establish versions of Descartes' rule of signs for radial basis function (RBF) neural networks. These RBF rules of signs provide tight bounds for the number of zeros of univariate networks with certain parameter restrictions. Moreover, they can be used to derive tight bounds for the Vapnik-Chervonenkis (VC) dimension and pseudo-dimension of these ...
openaire +1 more source
Automatical initialization of RBF neural networks
Chemometrics and Intelligent Laboratory Systems, 2007Although many methods are devoted to the design of Radial Basis Function Networks (RBFN), the lack of automatic approaches makes it difficult to generate suitable models in industrial applications. The object of this paper therefore proposes a deterministic method able to automatically select leaders or prototypes on which the RBFN design can be ...
Frédéric Ros +3 more
openaire +1 more source
Simultaneous Optimization of Weights and Structure of an RBF Neural Network
2006We propose here a new evolutionary algorithm, the RBF-Gene algorithm, to optimize Radial Basis Function Neural Networks. Unlike other works on this subject, our algorithm can evolve both the structure and the numerical parameters of the network: it is able to evolve the number of neurons and their weights.
Lefort, Vincent +3 more
openaire +2 more sources
A Growing Algorithm for RBF Neural Network
2009This paper presents a growing algorithm to design the architecture of RBF neural network called growing RBF neural network algorithm (GRBF). The GRBF starts from a single prototype randomly initialized in the feature space; the whole algorithm consists of two major parts: the structure learning phase and parameter adjusting phase.
Han Honggui, Qiao Junfei
openaire +1 more source
On the implementation of RBF technique in neural networks
Proceedings of the conference on Analysis of neural network applications, 1991Mohamad T. Musavi +3 more
openaire +1 more source
An efficient multilayer RBF neural network and its application to regression problems
Neural Computing and Applications, 2021Qinghua Jiang +2 more
exaly