Stochastic artificial neural network for magdm problem solving in intuitionistic fuzzy environment

Abstract

In this work, we have presented the decision-making models based on ANN, which takes argument pairs, of the intuitionistic fuzzy values and defuzzifies the decision matrices and create Stochastic matrices for producing input for computations of ANN. Concepts from Stochastic processes namely Markov chains and limiting distributions are discussed in detail in this research work and has been applied for effective decision making in complex situations. The numerical illustration provided in this work will be solved using the Markov chain models and some linear space techniques and applied in Artificial Neural Network (ANN). A new Algorithm is also developed for solving the MAGDM problems applying the proposed methods. The Numerical illustrations are solved with defuzzyfication operators and the results are recorded for effectiveness and comparisons are made with some existing methods. The new method proves to be more effective than the previous methods of ANN for MAGDM problems