Gas Turbine Power Prediction Based on Elman Neural Network
Power forecast of gas turbine is significant for breakdown prediction. For gas turbine failure prediction, this paper proposes a power prediction method based on Elman neural network. Experimental data are from the real data of a power plant, this paper selects the attributes relevant to power. Through comparative experiments, using suitable preprocessing method and input data, and setting the suitable number of neurons in hidden layer, this paper develops a gas turbine power prediction model based on Elman neural network. Finally, compared with back propagation (BP) network and radial basis function (RBF) network, this paper verifies the effectiveness of Elman neural network.
Elman neural networkgas turbine power predictionneural network
国家科技期刊平台
NSTL
万方数据
维普
