  In this paper we introduce a new symbolic type neural tree network called
symbolic function network (SFN) that is based on using elementary functions to
model systems in a symbolic form. The proposed formulation permits feature
selection, functional selection, and flexible structure. We applied this model
on the River Flow forecasting problem. The results found to be superior in both
fitness and sparsity.
