康雷, 徐南荣. 基于误差反馈的组合式人工神经网络的发电生产过程辨识[J]. 信息与控制, 1999, 28(5): 327-332.
引用本文: 康雷, 徐南荣. 基于误差反馈的组合式人工神经网络的发电生产过程辨识[J]. 信息与控制, 1999, 28(5): 327-332.
KANG Lei, XU Nan-rong. IDENTIFICATION OF GENERATING PROCESS BASED ON COMBINED ERROR FEEDBACK ARTIFICIAL NEURAL NETWORK[J]. INFORMATION AND CONTROL, 1999, 28(5): 327-332.
Citation: KANG Lei, XU Nan-rong. IDENTIFICATION OF GENERATING PROCESS BASED ON COMBINED ERROR FEEDBACK ARTIFICIAL NEURAL NETWORK[J]. INFORMATION AND CONTROL, 1999, 28(5): 327-332.

基于误差反馈的组合式人工神经网络的发电生产过程辨识

IDENTIFICATION OF GENERATING PROCESS BASED ON COMBINED ERROR FEEDBACK ARTIFICIAL NEURAL NETWORK

  • 摘要: 本文主要研究人工神经网络在辨识实际工业系统中的应用.由于辨识的对象是一个动态系统,所以着重对人工神经网络在辨识工业生产过程的动态特性作了分析.本文以发电生产过程为背景,针对不同负荷下发电生产工况的特点,提出了用子神经网络分别辨识不同负荷下的发电生产过程.在考虑系统稳定的前提下,本文提出引入误差反馈来训练人工神经网络辨识模型的方法.

     

    Abstract: This paper mainly researched the application of artificial neural network in real industrial systems. Because the object is a dynamic system, so we discussed the dynamic characteristics of artificial neural network used in identifying industrial process specially. With the background of power generating process, considering the characteristic of different bear, the paper proposed a novel method to identify the model that used sub network to identify the mathematics model of generating process in different loads. Considering the stability of the system, this paper introduced a new method to train neural network models with error feedback.

     

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