A Fuzzy Stochastic Model for a Markov Process

Abstract

In this paper, a combination of sequential Markov theory and cluster analysis, which determines inputs the Markov model of states, was the link between these two models by proposing Markov model formulated based on the principles of clustering Fuzzy, and comparison with the Markov model formulated based on clustering . It was also rely on the algorithm of K-Means clustering was Fuzzification to make a comparison. The practical side was applied to the caloric ratio in fruits and vegetables, it was noted that the Stationary distribution matrix of states of the Markov model formulated on the basis of clustering Fuzzy stabilized faster than the Markov model formulated on the basis of clustering, as was observed ratio stability of fruits and vegetables under study on low-calorie attribute is greater than the stability of the high-calorie attribute.