Personalized Navigation of Electric Vehicle Charging Station Based on Collaborative Filtering

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Abstract
At present, the scale of development of new energy vehicles in China is far below the requirements of the 13th Five-Year Plan. More consumers hold a wait-and-see attitude towards purchasing new energy vehicles. One of the reasons is that users have the problem of "difficult to find charging piles" and charging navigation when they have charging needs. Therefore, this paper combines the historical operation data of charging stations, uses the deep learning method to optimize the real-time forecast of the number of vehicles arriving at charging stations, and combines the historical charging data of users, uses the collaborative filtering algorithm to get the user recommendation list. Finally, the user selection preferences, driving distance and time are considered comprehensively to provide personalized charging navigation services for users.

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