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A neural network based fuzzy set model for organizational decision making

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2 Author(s)
Wang, S. ; Fac. of Bus., New Brunswick Univ., St. John, NB, Canada ; Archer, N.P.

A neural network based fuzzy set model is proposed to support organizational decision making under uncertainty. This model incorporates three theories and methodologies: classical decision-making theory under conflict, as suggested by Luce and Raiffa (1957), the fuzzy set theory of Zadeh (1965, 1984), and a modified version of the backpropagation (BP) neural network algorithm originated by Rumelhart et al. (1986). An algorithm that implements the model is described, and an application of the model to a real data example is used to demonstrate its use

Published in:

Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on  (Volume:28 ,  Issue: 2 )

Date of Publication:

May 1998

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