Application of Elman Neural Network and SARIMA Model to Modeling Road Traffic Accident in the Kurdistan Region of Iraq
Abstract
Road traffic and deaths accidents are the most complex and dangerous system of all road systems that people deal with on a daily basis. In addition to the loss of life, there is also a lot of material damage to the society. Therefore, we aim to study this effective topic through the Box-Jenkins model and the Elman Neural Network which are very appropriate to choose the best and most appropriate model for the number of accidents and the number of deaths from traffic accidents in the Iraqi Kurdistan Region according to monthly during the years (2014-2021).Finally, we compared the results between both models. It was concluded that the results of the Elman model (1:2,5) are better than the SARIMA (1,1,1)(0,1,1)12 model for the number of traffic accidents, and the results of the Elman(1:2,3) model are better than the SARIMA (0,1,1)(1,1,2)12 model for the number of deaths from traffic accidents based on statistical measures (RMSE, MAE, MAPE), which we used it for comparison. Statistical analysis is performed using the software (Statgraphics V.19) and the program (Matlab V.18a)
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