A neural network model of optimal scheduling system of public utility buses in Epifanio Delos Santos Avenue (EDSA)

This paper presents the artificial neural network model for the transportation system in Epifanio Delos Santos Avenue. Intelligent transportation aims to optimize the transportation system in Metro Manila. It will enhance productivity among public commuter and bus companies. The goal of this model is create an effective bus scheduling and dispatch system. This scheme will result in shorter waiting time for the passengers in every bus stop yielding a lessened travel time. Data from transportation survey will be the basis of the neural network model. MATLAB nftool is used in the development of the model. Levenburg-Marquardt backpropagation algorithm is employed in training data sets. The accuracy of the model is tested using Mean-Square Error and the reliability is measured using regression during testing.