TRAFFIC PRODUCTION MODEL USING MULTIPLE REGRESSION ANALYSIS AND RADIAL BASIS FUNCTION NEURAL NETWORK
In order to establish this model, several independent variables of aggregate level and dependent variables have been taken into account for traffic production of a region for a period of 24 hours. The objective of this paper is to identify and estimate the main variables which are significant for development of a suitable model for forecasting the traffic production for Anamorava region. Establishment and assessment of a model will be done using techniques such as Multiple Regression Analysis (MRA) and Radial Basis Function Neural Network (RBFNN). The results gained according to these two techniques will be compared to find out differences. In this regard performance analysis through indicators R2, ME, RSME which are also used to show errors in forecasting. The results are in favour of RBFNN model because it performs better than MRA in forecasting traffic production.