Neural Network Forecasting Time Sequence of the Power Plant

Neural network applied in power plant forecasing time sequence does not need stability hypothesizing.It studies interior laws of sequence from stylebooks of sequence,then builds a proper plant time sequence model.With neural network,the process to seek sequence laws is changed into a non linear optimizing problem of non linear mapping by R n→R m approach.The stable BP algorithmic means improved can obtain satisfying results.Forecasting sequence is more precise if historical input is increased properly.Examples have indicated that neural network can forecast plant time sequence better.Figs 5,tables 3 and refs 6.