A hybrid fuzzy-neuro model for preference-based decision analysis

Abstract

A hybrid fuzzy-neuro model that combines frame-based fuzzy logic system and neural network learning paradigm, hereinafter called FRN, is proposed to support innovative decision analysis (selection and assessment) process. The FRN model exploits the merits of reasoning from a frame-based fuzzy expert system in combination with preference-based learning derived from a supervised neural network. The FRN has proven to be useful and practical in filtering out all possible decision analyses. A salient feature of FRN is its ability to adapt to user's sudden change of preference in the midst of model implementation. A case study on the decision analysis (assessment and selection) of preference-based product is included to illustrate the implementation of FRN model. © Springer-Verlag Berlin Heidelberg 2004.