基于自动聚类和有监督学习算法的加热炉状态识别器设计

Design on Reheating Furnace State RecognizerBased on Auto Class andSupervisory Learning Algorithm

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.