Prediction of passenger movement indexes using Holt Winters Markov chain model

In order to predict the values of passengers movement indexes which enjoy seasonal changes, this research uses Holt Winters Markov chain model, which is a combination of Markov chain and Holt Winters models. In this regard, Data on the number of moved passengers and the number of made trips indexes are analyzed in Bushehr Province during the seasons of 1387 to 1391. First, Data on the each indexes of the studied intervals divided into two parts, then the second part data were predicted using Holt Winters model. In the next step, by calculating and classifying the errors of the actual and predicted values, Holt Winters Markov chain model is used in order to predict the Index values based on probabilities of errors mode and also improve the performance of Holt Winters model in prediction. The results obtained from the Comparison of two models of Holt Winters and Markov chain Holt Winters shows that Holt Winters Markov chain model is more accurate at predicting.