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-Elman 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 method to conduct training)has.So this model enhances the prediction accuracy and convergence speed

which is more suitable for field application.