Analysis of Economic Used Car Price Evaluation Method Based on PSO-BP Neural Network
This paper proposes a price evaluation model based on principal component analysis(PCA)and particle swarm optimization(PSO)to address the issue of BP neural network being prone to falling into local minima when predicting second-hand car prices,as well as the correlation between price influencing factors.This article uses the 10 principal components after PCA dimensionality reduction as evaluation parameters that affect second-hand car prices.Based on BP neural network,an economic second-hand car price evaluation model is es-tablished,and particle swarm optimization algorithm is used to optimize the weights and thresholds of the net-work,further improving the prediction accuracy of the network.This model to some extent overcomes the short-comings of BP neural network and provides a reference for the evaluation of second-hand car prices.
Economical used carValuation modelBP neural networkPrincipal Component Analysis(PCA)Particle Swarm Optimization(PSO)
万方数据
维普
