In this paper, we discuss some new methods for combining different outputs from several feed forward neural networks into a final output. We generalize the BADD defuzzification method (G-BADD) to obtain substantial improvement in system output. It is compared with the ordinary BADD-, Sugeno- and the MOM-methods. The use of the fuzzy integral, as a selection tool when deciding which networks are to be used in the combination, is introduced.