%0 Journal Article
%T Identification and Steady-State Hierarchical Optimization Method for Large-Scale Industrial Systems with Neural Network<br>基于神经网络的工业大系统辨识及稳态递阶优化方法
%A Li Yuqiao
%A Wan Baiwu
%A Liang Tianpei
%A <br>李玉桥
%A 万百五
%A 梁天培
%J 自动化学报
%D 1996
%I 
%X In order to do steady-state hierarchical optimization for large-scale industrial systems, the steady-state model of the system must be obtained. By means of neural network, this paper presents a dynamic identification method for steady-state models of large-scale industrial systems with neural network, and proposes a way for modelling. For improving convergence, this paper firstly introduces Lagrange function to solve constraint problem in large-scale system optimization, secondly constructs the hierarchical optimization networks for large-scale industrial systems with Hopfield network.
%K Steady-state hierarchical optimization
%K Hopfield neural network
%K feedforward neural network
%K large-scale industrial system<br>稳态递阶优化
%K 神经网络
%K 工业大系统
%K 辨识
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=AE236B1361C05343CD1A7F4D3A343CB8&yid=8A15F8B0AA0E5323&vid=BC12EA701C895178&iid=0B39A22176CE99FB&sid=A58CF3BAE79427D0&eid=7EBE588F611589FC&journal_id=0254-4156&journal_name=自动化学报&referenced_num=1&reference_num=3