OLIVEIRA, M. A.; OLIVEIRA, Mariana Alves.
Resumen:
In Brazil, road accidents are one of the major social and public health problems in the country.
In Paraíba, in particular, it is no different, the path that connects the city of Campina Grande to
the state's backlands brings expressive numbers. One of the forms of mitigation that has been
studied is the application of neural networks for the prediction of accidents, the objective of this
project being to develop an artificial neural network model to predict the frequency of accidents
on single-lane highways on the BR-230 with stretch from the municipality of Campina Grande
to the municipality of Cachoeira dos Índios, in the state of Paraíba. For comparative purposes,
three different forms of data analysis were used from a neural network chosen based on the
results obtained in tests, which correspond to the analysis with error margins with ranges
ranging from 5 to 30 km, the analysis dividing the highway in stretches of 5 to 30 km and the
third analysis consisted of dividing the highway into stretches between municipalities. This
analysis procedure by different methods allowed us to conclude that the best way to assess
stretches where intervention with safety measures is necessary is to divide the highway between
its municipalities, resulting in larger extensions with a higher rate of correctness for the neural
network. Based on the results it was possible to observe that the stretch where accidents occur
most is between the municipality of Sousa and Cachoeira dos Índios, passing through
Cajazeiras, where there is a greater concentration of cases taking into account the
proportionality of the stretch.