热力发电Issue(10)：90-94,5.DOI:10.3969/j.issn.1002-3364.2014.10.090
提高汽轮机排汽焓在线预测精度的 GA-Elman 神经网络算法
A GA-Elman neural network algorithm which can improve online prediction accuracy of exhaust enthalpy for steam turbines
摘要
Abstract
By taking use of good optimizing ability of the genetic algorithm (GA),the dynamic recurrent neural network (Elman)of steam turbine exhaust enthalpy was optimized and a GA-Elman neural network prediction model was established.Taking a 350 MW unit steam turbine as the example,online calculation for the turbine exhaust enthalpy was conducted by applying this model.The results show that:this GA-El-man neural network model overcomes such problems as easy to fall into local minimum,slow convergence speed and low precision that the conventional Elman neural network (which applies gradient descent meth-od to conduct training)has.So this model enhances the prediction accuracy and convergence speed,which is more suitable for field application.关键词
汽轮机/排汽焓/在线计算/预测精度/Elman/GAKey words
steam turbine/exhaust enthalpy/online calculation/prediction accuracy/Elman/GA分类
能源科技引用本文复制引用
王建国,赵帅,王广雨..提高汽轮机排汽焓在线预测精度的 GA-Elman 神经网络算法[J].热力发电,2014,(10):90-94,5.基金项目
国家自然科学基金资助项目(51176028) （51176028）
吉林省自然科学基金资助项目(201115179) （201115179）
