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

Shuhao Sun; Hong Zhou; Junjie Ji; Siye Liu

doi:10.1117/12.2640941

2 December 2022 Research on residual value prediction of new energy second-hand cars based on prophet multivariate time series model

Shuhao Sun, Hong Zhou, Junjie Ji, Siye Liu

Author Affiliations +

Proceedings Volume 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022); 122880O (2022) https://doi.org/10.1117/12.2640941
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 2022, Zhuhai, China

Abstract

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%.

Citation Download Citation

Shuhao Sun, Hong Zhou, Junjie Ji, and Siye Liu "Research on residual value prediction of new energy second-hand cars based on prophet multivariate time series model", Proc. SPIE 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 122880O (2 December 2022); https://doi.org/10.1117/12.2640941

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