This paper analyzes the characteristics of vehicle
breakdown duration and the relationship between
the duration and vehicle type, time, location, and
reporting mechanisms. Two models, one based on
fuzzy logic (FL) and the other on artificial neural networks
(ANN) were developed to predict the vehicle
breakdown duration. One advantage of these methods
is that few inputs are needed in the modeling.
Moreover, the distribution of the duration does not
affect the results of the prediction. Predictions were
compared with the actual breakdown durations
demonstrating that the ANN model performs better
than the FL model. In addition, the paper advocates
for a standard way to collect data to improve the
accuracy of duration prediction
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