Neural networks for analyzing service quality in public transportation
This paper presents a new approach to evaluating service quality in public transport systems using Artificial Neural Networks (ANN). ANN analysis represents a powerful methodology because its high capability for prediction and due to it does not require a pre-defined model. This study rises a well-understanding about different categories of attributes that have a greater or lesser impact on transit service quality. Three different algorithms are used to validate and corroborate the outcomes.
neural networks service quality ann bus transit mlp profile perturb connection weights