Abstract
In order to reduce the subjectivity and make sure the online car-hailing evaluation results more authentic and credible, an evaluation index system is constructed from five dimensions of the safety, cost, time, reliability and empathetic, and then a BP neural network model is proposed to solve it. Through the supervised model training of SP survey data, the maximum error between the network output and the actual results no more than 3.68%, which can meet the requirements of online car-hailing service quality evaluation. Finally, a mathematical statistical analysis method is proposed to comprehensive evaluate the online car-hailing service quality. The results show that the evaluation index system is scientific and reasonable, and the model can effectively improve the objectively of the evaluation results and reflect the quality level of online car-hailing service.
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