摘要
提出了一种加热炉状态识别器的设计方法 ,用自动聚类的方法对数据样本进行分类 ,并以聚类结果为学习样本 ,建立状态识别神经网络。利用该状态识别器对实际数据进行分类 。
A new algorithm called auto class and supervisory learning is proposed as the learning method for neural networks of reheating furnace state recognition.The recognizer is used for classifying the real data.The results demonstrate that the speed of recognition is fast and the accuracy is high.
出处
《河北工程技术高等专科学校学报》
2002年第3期10-13,18,共5页
Journal of Hebei Engineering and Technical College Quarterly
