Prediction of used car prices using back propagation neural network model based on mean encoding

Dewei Kan; Leilei Jiang; Chunhao Liu; Zhimin Yang; Dongming Song

doi:10.1117/12.2655828

12 January 2023 Prediction of used car prices using back propagation neural network model based on mean encoding

Dewei Kan, Leilei Jiang, Chunhao Liu, Zhimin Yang, Dongming Song

Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 125092U (2023) https://doi.org/10.1117/12.2655828
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China

Abstract

With the growth of the used car market and the development of e-commerce platforms, the need for accurate valuation of used car prices is becoming more urgent. Accuracy of price evaluation is the key to the success of used car transactions. At present, the common methods are manual experience method, Monte Carlo method, etc. Among them, manual experience method and multi-attribute decision method are more mature and widely used in traditional pricing method, but they have some disadvantages such as large computation amount and low accuracy. Aiming at the above problems, a BP neural network model based on mean encoding is designed in this paper. After extracting the features of the model, BP neural network is used to study the pre-processing data to predict the price for the network output. In this paper, a real used car trading dataset was used to test the model. The 2 R error is 0.976. Compared with the SVM and the decision tree model, this model is more accurate.

Citation Download Citation

Dewei Kan, Leilei Jiang, Chunhao Liu, Zhimin Yang, and Dongming Song "Prediction of used car prices using back propagation neural network model based on mean encoding", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 125092U (12 January 2023); https://doi.org/10.1117/12.2655828

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