STUDY AND COMPARISON OF ENSEMBLE FORECASTING BASED ON ARTIFICIAL NEURAL NETWORK

In term so fanartificial neural net work(ANN), an ensemble forecasting for a number of submodels of the same predict and is established, and consensus forecast expressions of the regressing, average and weighted meanare formulated with the aid of the same submodels. Results show the ANN is superior in fittings and predictions compared to the submodels and other consensus forecast due to its self-adaptive learning and non-linear mapping. The ANN'sensemble fo recasting is easy application in such a way to ascertain weighting coefficient, thus providing a new-line for the research of prediction integrated on long-term forecasting of flood and drought.