FNN model for IT Professionals Prequalification Decisions

Abstract

A Fuzzy Neural Network (FNN) model, combining both the fuzzy set and neural network theories, has b een developed
aiming to improve the objectives of I.T professionals’ analytical skills and prequalification. Through the FNN theory, the
fuzzy rules as used by the prequalifiers can be identified and the corresponding membership functions can be
transformed. Some cases with detailed decision criteria for prequalifying the I.T Professionals were collected. These
cases were used for training and testing the FNN model in their Project -Management. The performance of the FNN
model was compared with the original results produced by the prequalifiers and those generated by the general feed
forward neural network (GFNN, (i.e.) a crisp neural network) approach. These results indicate the applicability of the
neural network approach for I.T professionals prequalification and the benefits of the FNN model over the GFNN model.