Self-organizing modeling in forecasting daily river flows

摘要

In a new approach, which corresponds in a better way to the actions of human nervous system, the connections between several neurons are not fixed but change in dependence on the neurons themselves. This article presents a GMDH (group method of data handling) algorithm with active neurons. These neurons are able, during the learning or self-organizing process, to estimate which inputs are important to minimize the given objective function of the neuron. The nonlinear GMDH model approach is shown to provide better representation of the daily average water inflow forecasting, than the models based on Box-Jenkins method, currently in use in the Brazilian Electrical Sector.