The Estimations of Mechanical Property of Rolled Steel Bar by Using Quantum Neural Network

被引：0
|
作者：
Yang, Jen-Pin
Chen, Yu-Ju
Huang, Huang-Chu
Tsai, Sung-Ning
Hwang, Rey-Chue
机构：
来源：
SIXTH INTERNATIONAL SYMPOSIUM ON NEURAL NETWORKS (ISNN 2009) | 2009年 / 56卷
关键词：
Estimations; Mechanical property; Rolled steel bar; Quantum neural network; LOAD FORECASTER;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the estimations of mechanical property of rolled steel bar by using quantum neural network (QNN) were proposed. Based on the learning capability of neural network, the nonlinear, complex relationships among the steel bar, the billet materials and the control parameters of production could be automatically developed. Such an artificial intelligent (AI) estimator then can help the operation technician to set the related control parameters of rolling process. Not only the quality of steel bars could be improved, but also the cost of bar's production could be greatly reduced.
引用
收藏
页码：799 / 806
页数：8
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