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- W2046350129 abstract "This paper analyzes the characteristics of vehiclebreakdown duration and the relationship betweenthe duration and vehicle type, time, location, andreporting mechanisms. Two models, one based onfuzzy logic (FL) and the other on artificial neural networks(ANN) were developed to predict the vehiclebreakdown duration. One advantage of these methodsis that few inputs are needed in the modeling.Moreover, the distribution of the duration does notaffect the results of the prediction. Predictions werecompared with the actual breakdown durationsdemonstrating that the ANN model performs betterthan the FL model. In addition, the paper advocatesfor a standard way to collect data to improve theaccuracy of duration prediction." @default.
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- W2046350129 date "2005-01-01" @default.
- W2046350129 modified "2023-09-23" @default.
- W2046350129 title "Vehicle breakdown duration modelling" @default.
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