In this paper, the problem of system identification for the lateral motion of a strip in hot finishing mill is investigated. The movement is affected by various asymmetric factors with respect to rolling force. Not only that, the tension between rolling mills determines the direction of strip's moving. Consequently, the movement of a strip is complex dynamics with rolling condition, tension and other phenomena. To identify a neural network type system model in the existence of both uncertain parameters and nonlinear signals, deep learning based modelling is employed. ? 2016 Institute of Control, Robotics and Systems - ICROS.11Nscopu
The paper presents a model for predicting the roll wear in the hot rolling process. It includes all ...
This paper is intended to develop an artificial neural network (ANN) based model of material removal...
The paper reports the results of artificial neural network modelling of vibration in. a milling proc...
The paper presents a model based on neural networks which is able to predict the time required to pa...
Applications of neural networks in the rolling of steel are reviewed. The first papers on the topic ...
This work describes the application of neural networks in the modeling of hot rolling processes. Thi...
To address the problem that a deep neural network needs a sufficient number of training samples to h...
Abstract:-Recent developments, focused on the optimization of machining processes, through an effect...
The mathematical modeling of the rolling process involves several parameters that may lead to non-li...
The aim of this study is to predict surface roughness in end milling of AISI 1040 steel. In realisin...
This study is aimed at getting simplified model of mill filling technological process of fine crushi...
The digital industrial revolution calls for smart manufacturing plants, i.e. plants that include sen...
Surface roughness and machining accuracy are essential indicators of the quality of parts in milling...
reservedSteel wire rods are a key product of the steel industry with multiple applications such as s...
The single stand rolling mill governing equation is a non-linear function on several parameters (inp...
The paper presents a model for predicting the roll wear in the hot rolling process. It includes all ...
This paper is intended to develop an artificial neural network (ANN) based model of material removal...
The paper reports the results of artificial neural network modelling of vibration in. a milling proc...
The paper presents a model based on neural networks which is able to predict the time required to pa...
Applications of neural networks in the rolling of steel are reviewed. The first papers on the topic ...
This work describes the application of neural networks in the modeling of hot rolling processes. Thi...
To address the problem that a deep neural network needs a sufficient number of training samples to h...
Abstract:-Recent developments, focused on the optimization of machining processes, through an effect...
The mathematical modeling of the rolling process involves several parameters that may lead to non-li...
The aim of this study is to predict surface roughness in end milling of AISI 1040 steel. In realisin...
This study is aimed at getting simplified model of mill filling technological process of fine crushi...
The digital industrial revolution calls for smart manufacturing plants, i.e. plants that include sen...
Surface roughness and machining accuracy are essential indicators of the quality of parts in milling...
reservedSteel wire rods are a key product of the steel industry with multiple applications such as s...
The single stand rolling mill governing equation is a non-linear function on several parameters (inp...
The paper presents a model for predicting the roll wear in the hot rolling process. It includes all ...
This paper is intended to develop an artificial neural network (ANN) based model of material removal...
The paper reports the results of artificial neural network modelling of vibration in. a milling proc...