Discrete hopfield neural networks for evaluating service quality of public transit

Abstract

In this paper, we present Discrete Hopfield neural networks (DHNN) for evaluation service quality of public transit. First, we proposed an ideal service quality evaluation index system of public transit. Then, the survey conducted as a support to the study was realized in the winter of 2012 from Oct 8 to Oct 15 in the city of Nanjing. At last, the validity of the proposed methodology has been confirmed by the experimental results of 5 bus routes chosen at random. The results show that it is essential to capture more detailed information about service quality ofpublic transit from passenger perceptions with DHNN. © 2014 SERSC.