摘要
转炉炼钢过程是一个非常复杂的物理化学变化过程,无法用数学方程线性描述。人工神经网络因具有很强的非线性处理能力且具有较强的容错性,从而广泛应用于冶金过程中。本文主要介绍了人工神经网络在转炉炼钢中的应用现状,通过对BP神经网络和RBF神经网络在转炉炼钢中的应用分析,指出人工神经网络技术的应用将进一步提高转炉炼钢过程的自动化水平。
BOF steelmaking is a very complex physical chemistry process which can not be described with mathematical equations of linear. Artificial neural network can be used in metallurgical process due to its ability of dealing with non-linear problems and strong fault-tolerance. The present application of ar- tificial neural network was briefly introduced on B0F steelmaking process. According to the analysis of BP neural network and RBF neural network in BOF, it pointed out that the application of artificial neural network will improve the automatic control level of BOF steelmaking process.
出处
《冶金丛刊》
2010年第1期40-42,共3页
Metallurgical Collections
关键词
转炉炼钢
BP神经网络
静态控制
预报
BOF steelmaking
BP neural network
static control
prediction
