Modelling Accessibility based on Urbanization using Artificial Neural Networks (ANN)

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T. Pavan Kumar
K. M. Lakshmana Rao


The present study involves modelling the accessibility index with respect to the traffic volume, Right of Way width and Population density. It also involves the collection of number of different types of opportunities like schools, hospitals, ATMs, bus-stops and parks to determine the accessibility index. Two different methods are used in the study such as Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) to develop models in order to predict the accessibility index. Based on the R2 value obtained in the models, it is observed that ANN has better prediction capability than MLR model. The study acts as a guide to the urban transportation planners to understand the change in accessibility index when there is a change in urbanization variables.

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How to Cite
Kumar, T. P. ., & Lakshmana Rao, K. M. . (2023). Modelling Accessibility based on Urbanization using Artificial Neural Networks (ANN). International Journal on Recent and Innovation Trends in Computing and Communication, 11(9s), 272–275.


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