摘要
本文以粗糙集理论为基础,运用可辨识矩阵对薄膜蒸发器参数的特征参数进行约简,过滤冗余参数,结合神经网络学习方法,用ActiveXDLL和COM组件生成技术实现了VisualBasic与Matlab的链接,建立一种薄膜蒸发器工况预警系统,并对工况预测研究。结果表明,该系统提高了对薄膜蒸发器工况的预警的效率和正确性,为实际应用以及开发智能薄膜蒸发器工况预警系统创造条件。
In order to establish a thin-film evaporator operating early warming system based on the rough set theory and predicts the working conditions of the thin-film evaporator, it is appropriate the to simplify the characteristic parameters using the method of discernibility matrix, integrate the algorithm of neural network and adopt the generation technique of ActiveX DLL and COM components to connect Visual Basic and Matlab. The result shows that the proposed system can improve efficiency and the accuracy of thin-film evaporator operating early warming for the practical application and the development of the intellective operating early warming systems of the thin-film evaporator.
出处
《微计算机信息》
2009年第32期33-35,共3页
Control & Automation
关键词
粗糙集理论
神经网络
薄膜蒸发器
工况预警
rough set theory
neural network
thin-film evaporator
operating early warming
