Nowadays, the rapid development of new energy vehicles has also driven the new energy second-hand car market. This study aims to solve the current problems of messy residual value evaluation of new energy second-hand cars, and better predict the residual value through the loss variables. It crawled the data from the second-hand car website through crawlers and found that new energy second-hand cars have trends, periodicity, and some additional effects. Therefore, this study adopted the Prophet Multivariate Time Series model for prediction whose input is the licensing time and kilometers, and output is the predicted price. Through trend comparison and accuracy evaluation, the model showed better prediction performance whose prediction accuracy of the residual value of new energy second-hand vehicles can reach 96%.


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    Title :

    Research on residual value prediction of new energy second-hand cars based on prophet multivariate time series model


    Contributors:
    Sun, Shuhao (author) / Zhou, Hong (author) / Ji, Junjie (author) / Liu, Siye (author)

    Conference:

    International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022) ; 2022 ; Zhuhai,China


    Published in:

    Proc. SPIE ; 12288


    Publication date :

    2022-12-02





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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