Abstrato

A novel T-FGM (1,1) forecasting model based on rbf neural network for water demand forecasting

Xinjun Wang

In order to forecast the water demand and enhance the utilization of water resources, based on the basic principle of Grey Model with First Order Differential Equation and one Variable (GM(1,1)), in this paper, a novel First-entry traversal Grey Model with First Order Differential Equation and one Variable (T-FGM(1,1)) was established byminimumtotal residual sum of square. Furthermore, A T-FGM(1,1)( First-entry traversal Grey Modelwith FirstOrderDifferential Equation and oneVariable)-RBF ( radial basis function) neural network model is established. The proposed model not only educes the unstable factors that influence the forecast, but also can interfuse the advantages in the uncertainty domain in neural network.