Results 221 to 230 of about 1,355,935 (279)

Analytic fuzzy RBF neural network

1998 Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.98TH8353), 2002
An analytic fuzzy neural network with a modified RBF architecture and fuzzy weights is introduced. The fuzzy weights are non-symmetric fuzzy numbers. The learning algorithm is based on a gradient technique.
A. Kandel, H.-N. Teodorescu, D. Arotaritei   +2 more
openaire   +1 more source

Adaptive Computation Algorithm for RBF Neural Network

IEEE Transactions on Neural Networks and Learning Systems, 2012
A novel learning algorithm is proposed for nonlinear modelling and identification using radial basis function neural networks. The proposed method simplifies neural network training through the use of an adaptive computation algorithm (ACA). In addition, the convergence of the ACA is analyzed by the Lyapunov criterion. The proposed algorithm offers two
Hong-Gui, Han, Jun-Fei, Qiao
openaire   +2 more sources

New dynamic RBF neural network controller

Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826), 2005
It isn't very effective to use RBF neural network as controller to deal with dynamic systems. So a new dynamic radial basis function network including feedback unit is proposed. The universal approximation theorem of DRBF is proved according to Stone-Weierstrass theorem.
null Ya-Min Wan, null Sun-An Wang
openaire   +1 more source

A novel hybrid model based on VMD-WT and PCA-BP-RBF neural network for short-term wind speed forecasting

Energy Conversion and Management, 2019
Accurate short-term wind power forecasting is significant for rational dispatching of the power grid and ensuring the power supply quality. In order to enhance the accuracy of short-term wind speed prediction, a hybrid model based on VMD-WT and PCA-BP ...
Yagang Zhang, Bing Chen, Guifang Pan, Yuan Zhao   +3 more
semanticscholar   +1 more source

Evolving RBF Neural Networks

2001
Determining the parameters of a Radial Basis Function Neural Nerwork (number of neurons, and their respective centers and radii) is often done by hand, or based in methods highly dependent on initial values. In this work, Evolutionary Algorithms are used to automatically build a RBF NN that solves a specified problem.
V. M. Rivas, P. A. Castillo, J. J. Merelo   +2 more
openaire   +1 more source

Evaluation of English interpretation teaching quality based on GA optimized RBF neural network

Journal of Intelligent & Fuzzy Systems, 2020
Aiming at the problem of low accuracy of the current English interpretation teaching quality evaluation, a teaching quality evaluation method based on a genetic algorithm (GA) optimized RBF neural network is proposed.
Chen Lu, Beina He, Rui Zhang
semanticscholar   +1 more source

Orthogonal RBF Neural Network Approximation

Neural Processing Letters, 1999
The approximation properties of the RBF neural networks are investigated in this paper. A new approach is proposed, which is based on approximations with orthogonal combinations of functions. An orthogonalization framework is presented for the Gaussian basis functions. It is shown how to use this framework to design efficient neural networks.
openaire   +2 more sources

Post-training on RBF neural networks

Nonlinear Analysis: Hybrid Systems, 2007
Radial basis function neural networks are the most widely used networks due to their rapid training, generality, and simplicity. The nature of these networks necessitates some types of errors which can never be removed by traditional training algorithms.
Faridoon Shabaninia, Mehdi Roopaei, Mehdi Fatemi   +2 more
openaire   +1 more source

Pulsed VLSI for RBF neural networks

Proceedings of Fifth International Conference on Microelectronics for Neural Networks, 2002
This paper presents simulation and hardware results from cascadable circuits for pulsed Radial Basis Function (RBF) neural network chips. The functionality of each circuit is clearly demonstrated from the hardware results and consideration is also given to the practical issues affecting the development of a pulsed RBF demonstrator chip.
D.J. Mayes, A.F. Murray, H.M. Reekie
openaire   +1 more source

Automatical initialization of RBF neural networks

Chemometrics and Intelligent Laboratory Systems, 2007
Although 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, Marco Pintore, Arnaud Deman, Jacques R. Chrétien   +3 more
openaire   +1 more source