Evaluation Method of Automobile Maintenance and Service Quality Based on Relevance Vector Machine

doi:10.3969/j.issn.1006-2475.2017.11.013

Abstract

Abstract: Aiming at the real performance appraisal requirement of comprehensive performance evaluation for maintenance and service quality at service stations (including 4S shops) which belong to automobile manufacturing enterprise, we use the relevance vector machine theoretical model algorithm to implement the evaluation of maintenance and service quality. Relevant experiments show that the relevance vector machine is better than the traditional artificial neural network, support vector machine and depth neural network for the evaluation of service quality of automobile service providers. This evaluation method improves the validity, timeliness and satisfaction of the fault treatment, and provides a good service provider for the after-sales service department of the automobile manufacturer. It provides a reference for the customers who are in good agreement with the cause of the failure. At the same time, the selection of evaluation indexes is more comprehensive and detailed, which makes the evaluation model more conducive to practical production applications.

Key words: evaluation method, automobile after-sales service, maintenance service quality, relevance vector machine

CLC Number:

TP391

SHI Yun, LOU Xin-yuan, ZENG Ming-hua, WU Yan-ru. Evaluation Method of Automobile Maintenance and Service Quality Based on Relevance Vector Machine[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2017.11.013.

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