Modeling of textile manufacturing processes using intelligent techniques: a review
As the need for quickly exploring a textile manufacturing process is increasingly costly along
with the complexity in the process. The development of manufacturing process modeling has …
with the complexity in the process. The development of manufacturing process modeling has …
[图书][B] Control of complex systems
The world of artificial systems is reaching complexity levels that es cape human
understanding. Surface traffic, electricity distribution, air planes, mobile communications …
understanding. Surface traffic, electricity distribution, air planes, mobile communications …
Improved learning algorithms for mixture of experts in multiclass classification
Mixture of experts (ME) is a modular neural network architecture for supervised learning. A
double-loop Expectation-Maximization (EM) algorithm has been introduced to the ME …
double-loop Expectation-Maximization (EM) algorithm has been introduced to the ME …
Recurrent radial basis function network for time-series prediction
This paper proposes a Recurrent Radial Basis Function network (RRBFN) that can be
applied to dynamic monitoring and prognosis. Based on the architecture of the conventional …
applied to dynamic monitoring and prognosis. Based on the architecture of the conventional …
A spatial interpolation method based on radial basis function networks incorporating a semivariogram model
GF Lin, LH Chen - Journal of Hydrology, 2004 - Elsevier
Based on the combination of the radial basis function network (RBFN) and the
semivariogram, a spatial interpolation method, named improved RBFN, is proposed in this …
semivariogram, a spatial interpolation method, named improved RBFN, is proposed in this …
MELM-GRBF: A modified version of the extreme learning machine for generalized radial basis function neural networks
F Fernández-Navarro, C Hervás-Martínez… - Neurocomputing, 2011 - Elsevier
In this paper, we propose a methodology for training a new model of artificial neural network
called the generalized radial basis function (GRBF) neural network. This model is based on …
called the generalized radial basis function (GRBF) neural network. This model is based on …
Contribution à la surveillance des systèmes de production à l'aide des réseaux de neurones dynamiques: Application à la e-maintenance
R Zemouri - 2003 - theses.hal.science
Les méthodes de surveillance industrielle sont divisées en deux catégories: méthodes de
surveillance avec modèle formel de l'équipement, et méthodes de surveillance sans modèle …
surveillance avec modèle formel de l'équipement, et méthodes de surveillance sans modèle …
Estimation of elliptical basis function parameters by the EM algorithm with application to speaker verification
This paper proposes to incorporate full covariance matrices into the radial basis function
(RBF) networks and to use the expectation-maximization (EM) algorithm to estimate the …
(RBF) networks and to use the expectation-maximization (EM) algorithm to estimate the …
BYY harmony learning, structural RPCL, and topological self-organizing on mixture models
L Xu - Neural Networks, 2002 - Elsevier
The Bayesian Ying-Yang (BYY) harmony learning acts as a general statistical learning
framework, featured by not only new regularization techniques for parameter learning but …
framework, featured by not only new regularization techniques for parameter learning but …
Radial basis functional link nets and fuzzy reasoning
CG Looney - Neurocomputing, 2002 - Elsevier
We modify the architecture of radial basis function neural networks so as to also model
linear as well as the usual nonlinear input–output relationships. The resulting network learns …
linear as well as the usual nonlinear input–output relationships. The resulting network learns …