A layered after-sale quality evaluation model based on improved artificial neural network

Jichao Li, Haobin Shi, Xinru Li, Meng Xu

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In this paper, a model of quality evaluation of after-sale service based on improved artificial neural network is proposed. This model applies an improved analytic hierarchy process to determine the weight of the evaluation index system, and then employs the artificial neural network to evaluate the after-sale service quality. Aiming at the problem that the classical BP neural network has slow convergence speed and low learning efficiency, this paper uses an accelerated BP neural network learning algorithm based on momentum constants. Compared with the classical BP neural network, the accelerated neural network in this paper has higher learning efficiency. Finally, through the evaluation experiment of the automobile service quality, the evaluation model of service quality can be used to evaluate the quality of the After-sale service, which provides the scientific and effective guidance for the evaluation of the service quality of the automobile.

源语言英语
主期刊名Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence, CSAI 2018 - 2018 the 10th International Conference on Information and Multimedia Technology, ICIMT 2018
出版商Association for Computing Machinery
46-51
页数6
ISBN(电子版)9781450366069
DOI
出版状态已出版 - 8 12月 2018
活动2nd International Conference on Computer Science and Artificial Intelligence, CSAI 2018 - Shenzhen, 中国
期限: 8 12月 201810 12月 2018

出版系列

姓名ACM International Conference Proceeding Series

会议

会议2nd International Conference on Computer Science and Artificial Intelligence, CSAI 2018
国家/地区中国
Shenzhen
时期8/12/1810/12/18

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