Using wavelet neural network model product quality of continuous casting furnace and hot rolling mill

2004 ◽  
Author(s):  
Huanqin Li ◽  
Baiwu Wan
Keyword(s):  
Neural Network ◽  
Continuous Casting ◽  
Product Quality ◽  
Network Model ◽  
Neural Network Model ◽  
Hot Rolling ◽  
Rolling Mill ◽  
Wavelet Neural Network ◽  
Hot Rolling Mill

Application of wavelet neural network model based on genetic algorithm in the prediction of high-speed railway settlement

2015 ◽  
Author(s):  
Shihua Tang ◽  
Feida Li ◽  
Yintao Liu ◽  
Lan Lan ◽  
Conglin Zhou ◽  
...  
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Network Model ◽  
Neural Network Model ◽  
High Speed ◽  
Wavelet Neural Network ◽  
High Speed Railway ◽  
Model Based

scholarly journals Contribution to image restoration using a neural network model

2002 ◽  
Vol Volume 1, 2002 ◽  
Author(s):  
Karim Achour ◽  
Nadia Zenati ◽  
Oualid Djekoune
Keyword(s):  
Neural Network ◽  
Image Restoration ◽  
Network Model ◽  
Neural Network Model ◽  
Hopfield Neural Network ◽  
Optimization Method ◽  
Nous Proposons ◽  
International Audience ◽  
High Level

International audience The reduction of the blur and the noise is an important task in image processing. Indeed, these two types of degradation are some undesirable components during some high level treatments. In this paper, we propose an optimization method based on neural network model for the regularized image restoration. We used in this application a modified Hopfield neural network. We propose two algorithms using the modified Hopfield neural network with two updating modes : the algorithm with a sequential updates and the algorithm with the n-simultaneous updates. The quality of the obtained result attests the efficiency of the proposed method when applied on several images degraded with blur and noise. La réduction du bruit et du flou est une tâche très importante en traitement d'images. En effet, ces deux types de dégradations sont des composantes indésirables lors des traitements de haut niveau. Dans cet article, nous proposons une méthode d'optimisation basée sur les réseaux de neurones pour résoudre le problème de restauration d'images floues-bruitées. Le réseau de neurones utilisé est le réseau de « Hopfield ». Nous proposons deux algorithmes utilisant deux modes de mise à jour: Un algorithme avec un mode de mise à jour séquentiel et un algorithme avec un mode de mise à jour n-simultanée. L'efficacité de la méthode mise en œuvre a été testée sur divers types d'images dégradées.

Wavelet neural network model for river flow time series

2012 ◽  
Vol 165 (8) ◽  
pp. 425-439 ◽  
Author(s):  
Budu Krishna ◽  
Yellamelli Ramji Satyaji Rao ◽  
Purna Chandra Nayak
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Network Model ◽  
Neural Network Model ◽  
River Flow ◽  
Flow Time ◽  
Wavelet Neural Network
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