Recursive Implementation of Markov Model, A New Approach

Markov Model (MM) is a very effective statistical tool for predicting future behavior of a system. The higher the accuracy the more beneficial it becomes. A little increase in accuracy can lead to greater success rate. Improving this accuracy is a big challenge. In this paper we have proposed recursive implementation of MM to achieve better accuracy. We have designed and implemented the algorithm and found average 5% better accuracy than the existing algorithm. This increased accuracy can be helpful in the existing system where MM is used as prediction tool.