The Markov Error Correcting Method in Gray Neural Network for Power Load Forecasting

As the power load forecasting sequence has stochastic growth and nonlinear wave characteristics, grey neural network model can effective reflect the growth properties of the sequence and fit the nonlinear relation. Markov chain can easily embody the random characteristic of system by complex factors, so the Markov chain error correction method was introduce in this paper, the whole forecasting precision of the sequence was optimized, and the transfer matrix for the forecasting sequence was decided, then the accuracy for power load forecasting was greatly improved. Through the demonstration test, the precision is better than ingenuous grey neural network, the method in this paper have feasibility in practice.