摘要
针对传统宽展计算模型的固有缺陷 ,提出一种基于人工智能方法建立的“多层感知器”神经网络模型。离线仿真结果表明 ,神经网络模型预报精度优于传统方法。
In view of the innate defects of classical calculating models of spread and in order to enhance the width accuracy and the rate of the end products of hot rolling steel plate, the paper produced a method for spread forecast based on artificial neural network and established the neural network model with mutilayer sensors. The experiment result of out line simulation indicates the method introduced in this paper is better than classical methods.
出处
《轧钢》
2001年第1期13-15,共3页
Steel Rolling
关键词
热轧带钢
宽展预报
人工智能
多层感知器
hot rolling steel strip
breadth spread forecast
artificial neural network
mutilayer sensors
