Intelligent charging recommendation model based on collaborative filtering

Yingwei Zhao, Zhen Wang, Yunying Man, H. Wen, Wen Han, Peiyao Wang
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引用次数: 1

Abstract

In recent years, the development of new energy vehicles in the world has entered the industrial scale, but electric vehicles (EVs) have the disadvantage of short driving range due to the capacity of the battery, which need to supplement electric energy in charging stations. Although the number of charging piles for EVs is increasing day by day, its growth rate has not caught up with the charging demand for EVs. In order to provide personalized charging service for users with convenient power consumption and efficient charging, a set of intelligent recommendation model for EV charging is proposed based on collaborative filtering algorithm, which provides optimal charging method based on the user's historical behavior data.
基于协同过滤的智能收费推荐模型
近年来,全球新能源汽车的发展已进入产业化规模,但电动汽车由于电池容量不足,存在续驶里程短的缺点,需要在充电站补充电能。尽管电动汽车充电桩的数量日益增加,但其增长速度并没有跟上电动汽车的充电需求。为了给用户提供方便用电、高效充电的个性化充电服务,提出了一套基于协同过滤算法的电动汽车充电智能推荐模型,该模型基于用户的历史行为数据提供最优充电方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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