Neural networks for analyzing service quality in public transportation

作者：

Highlights：

• 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.

摘要

•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.

论文关键词：Service quality,Bus transit,Neural networks,ANN,MLP,Profile,Perturb,Connection Weights

论文评审过程：Available online 9 May 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.04.045