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A method of chained recommendation for charging piles in internet of vehicles

机译:一种用于车辆互联网上桩的链接建议的方法

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With the popularization of new energy electric vehicles (EVs), the recommendation algorithm is widely used in the relatively new field of charge piles. At the same time, the construction of charging infrastructure is facing increasing demand and more severe challenges. With the ubiquity of Internet of vehicles (IoVs), inter-vehicle communication can share information about the charging experience and traffic condition to help achieving better charging recommendation and higher energy efficiency. The recommendation of charging piles is of great value. However, the existing methods related to such recommendation consider inadequate reference factors and most of them are generalized for all users, rather than personalized for specific populations. In this paper, we propose a recommendation method based on dynamic charging area mechanism, which recommends the appropriate initial charging area according to the user's warning level, and dynamically changes the charging area according to the real-time state of EVs and charging piles. The recommendation method based on a classification chain provides more personalized services for users according to different charging needs and improves the utilization ratio of charging piles. This satisfies users' multilevel charging demands and realizes a more effective charging planning, which is beneficial to overall balance. The chained recommendation method mainly consists of three modules: intention detection, warning levels classification, and chained recommendation. The dynamic charging area mechanism reduces the occurrence of recommendation conflict and provides more personalized service for users according to different charging needs. Simulations and computations validate the correctness and effectiveness of the proposed method.
机译:随着新能源电动车(EVS)的推广,推荐算法广泛用于相对较新的电荷桩。与此同时,充电基础设施的建设面临着越来越多的需求和更严峻的挑战。随着车辆互联网(IOV)的无处不在,车间通信可以共享关于收费经验和交通状况的信息,以帮助实现更好的充电推荐和更高的能效。充电桩的建议具有很大的价值。然而,与此类建议书相关的现有方法考虑不充分的参考因素,并且大多数是所有用户都是推广的,而不是针对特定人群的个性化。在本文中,我们提出了一种基于动态充电区域机制的推荐方法,其推荐根据用户的警告水平的适当初始充电区域,并且根据EVS和充电桩的实时状态动态地改变充电区域。基于分类链的推荐方法根据不同的充电需求为用户提供更多个性化服务,并提高充电桩的利用率。这满足了用户的多级充电需求,并实现了更有效的充电计划,这对整体平衡有益。链接的推荐方法主要由三个模块组成:意图检测,警告级别分类和链接推荐。动态充电区域机制减少了推荐冲突的发生,并根据不同的充电需求为用户提供更多个性化服务。仿真和计算验证了所提出的方法的正确性和有效性。

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