A neural network based methodology for the prediction of roll force and roll torque in fuzzy form for cold flat rolling process

被引：27

作者：

Dixit, US ^{[1
]}

Chandra, S ^{[1
]}

机构：

[1] Indian Inst Technol, Dept Mech Engn, Gauhati 781039, India

来源：

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 2003年 / 22卷 / 11-12期

关键词：

cold flat rolling; neural networks; back propagation algorithm; prediction of roll force and roll torque;

D O I：

10.1007/s00170-003-1628-8

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Neural network models can be effectively used to predict any type of functional relationship. In this paper, a neural network model is used to predict roll force and roll torque in a cold flat rolling process, as a function of various process parameters. A strategy is developed to obtain a prescribed accuracy of prediction with a minimum number of data for training and testing. The effect of increasing the size of training and testing data set is also examined. After the prediction of most likely value, upper and lower bound estimates are also found with the help of the neural network. With these estimates, the predicted value can be represented as a fuzzy number for use in fuzzy-logic based systems.

引用

页码：883 / 889

页数：7

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