混合动力汽车消费者投诉数据库的规则挖掘

IF 2.4 3区 工程技术 Q3 TRANSPORTATION
Subasish Das, Zihang Wei, Anandi Dutta
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引用次数: 0

摘要

摘要混合动力汽车(HEV)是一项关键的交通颠覆性技术,在当前和未来的市场上有望得到广泛应用。许多国家正在推动混合动力汽车的成功。由于这些车辆的技术和设计与传统车辆有很大不同,因此了解与这些车辆相关的技术和车身相关问题也很重要。本研究使用美国国家公路交通安全管理局的车主投诉数据库来探索与混合动力汽车相关的潜在问题。获得的数据集根据他们参与交通事故的情况分为两组。本研究采用关联规则挖掘和文本挖掘方法对汽车消费者投诉数据进行分析。关联规则挖掘的结果显示,在碰撞相关车辆投诉数据集中,2010年至2021年间生产的混合动力全轮驱动汽车之间存在显著关联,这些汽车没有防抱死制动和巡航控制。1992年至1999年间生产的非混合动力汽车,配备巡航控制和防制动系统以及5-10个气缸,经常出现在与碰撞相关的投诉数据集中。与里程相关的问题和相对较旧的混合动力汽车(2000-2009)在非碰撞相关数据中占主导地位。文本挖掘方法的结果表明,刹车、里程、故障和碰撞是与碰撞相关的消费者投诉的关键特征,而刹车、电池、电源和召回是与碰撞无关的消费者投诉的关键特征。情绪分析结果显示,在与车祸相关的投诉报告中,负面情绪略高。这项研究的发现可以为这个尚未开发的研究领域提供一些见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rules mining on hybrid electric vehicle consumer complaint database
Abstract The hybrid electric vehicle (HEV) is a critical transportation disruptive technology that is expected to be widely adopted in the current and future marketplace. Many nations are promoting the success of HEVs. As the technologies and designs of these vehicles are significantly different from conventional vehicles, it is also important to understand the technical and body-related issues associated with these vehicles. This study used the National Highway Traffic Safety Administration’s vehicle owner’s complaint database to explore the potential issues associated with HEVs. The acquired dataset was divided into two groups based on their involvement in traffic crashes. The study applied association rule mining and text mining methods to analyze vehicle consumer complaint data. The results of association rule mining showed a significant association between hybrid electric all-wheel-drive vehicles manufactured between 2010 and 2021 that do not have anti-lock brakes and cruise control in the crash-related vehicle complaints dataset. Non-HEV vehicles, manufactured between 1992 and 1999, with cruise control and anti-braking systems as well as 5-10 cylinders, appeared frequently in the crash-related complaint dataset. Mileage-related issues and comparatively older HEVs (2000-2009) are dominant in non-crash-related data. The results from the text mining method show that brakes, mileage, failure, and crash are key features for consumer complaints related to crashes and brakes, battery, power, and recall are the key features for consumer complaints not related to crashes. The sentiment analysis results show slightly higher negative sentiments in complaint reports associated with crashes. The findings of this study can provide some insights into this unexplored research area.
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来源期刊
CiteScore
6.00
自引率
15.40%
发文量
38
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