Artificial Neural Network Approach to Simulation and Prediction of Traffic Congestion for Morkovian Queue with Single Server

Abstract

In this paper, a traffic congestion of Markovian queueing model with single server has been focussed for its simulation and prediction modelling by using artificial neural network that models the complex and non-linear relationship between input and output. Now a day, traffic congestion is a seriously growing issue as it increases travel time, air pollution, carbon dioxide emissions and extra fuel use because vehicular movement cannot run efficiently. The results of simulation can be compared with that of analytical methods in order to improve it. It can be useful as an application model for various areas including classification and prediction, data processing, image and pattern recognition, marketing, finance and management, medical and robotics etc.