摘要
针对隧道时变性与不确定性,提出一种基于BP神经网络预测风机频率的算法,通过频率预测开启风机,实现隧道通风自动化。在此算法基础上,运用MIV算法筛选有意义的输入参数。结果表明,经MIV算法优化后,BP神经网络算法预测风机频率有较高精确性,符合风机在隧道的运行特性,可应用于隧道通风。
In view of the time variability and uncertainty of the tunnel,this paper presents an algorithm based on BP neural network to predict the frequency of the fan.On the basis of this algorithm,the MIV algorithm is used to select the input parameters.The results show that the proposed algorithm has a high accuracy in predicting the frequency of the fan,and it can be used in tunnel ventilation.
作者
王中洋
孟宪伦
WANG Zhong-yang;MENG Xian-lun(School of Energy Science and Engineering,Henan Polytechnic University;School of Electrical Engineering and Automation,Henan Polytechnic University,Jiaozuo 454150,China)
出处
《软件导刊》
2018年第6期100-101,105,共3页
Software Guide
