Authors: V. M. Naidu, CSRK Prasad, M. Srinivas, T. Praveen Sagar
Abstract: Trip rate is defined as the ratio of the Total number of trips generated per day to the Total population of the considered area. While considering a city as a study area it is difficult to relate the amount of trips that originate in that study area and the amount of trips attracted towards the study area in a conventional manner. This study brings out some basic Travel parameters that helps in estimating the number of trips in a study area. Relationship between Travel parameters and Trip rate has been established using Artificial Neural Network (ANN) using different learning functions which reflects its performance level. In this study we have used learning functions TRAINLM, TRAINSCG which provided better results in establishing the relation between Trip rate and Trip rate parameters.
Keywords: - Artificial neural network, Trip rate (all-modes), Independent variables (Travel parameters) Trainlm, Trainscg, Multi-layer Feed Forward network, Feed Forward back propagation network.
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