Modeling of textile manufacturing processes using intelligent techniques: a review

Z He, J Xu, KP Tran, S Thomassey, X Zeng… - The International Journal …, 2021 - Springer
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 …

[图书][B] Control of complex systems

KJ Aström, P Albertos, M Blanke, A Isidori… - 2011 - books.google.com
The world of artificial systems is reaching complexity levels that es cape human
understanding. Surface traffic, electricity distribution, air planes, mobile communications …

Improved learning algorithms for mixture of experts in multiclass classification

K Chen, L Xu, H Chi - Neural networks, 1999 - Elsevier
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 …

Recurrent radial basis function network for time-series prediction

R Zemouri, D Racoceanu, N Zerhouni - Engineering Applications of …, 2003 - Elsevier
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 …

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 …

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 …

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 …

Estimation of elliptical basis function parameters by the EM algorithm with application to speaker verification

MW Mak, SY Kung - IEEE Transactions on Neural Networks, 2000 - ieeexplore.ieee.org
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 …

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 …

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 …