Car Sales Volume Prediction Based on Particle Swarm Optimization Algorithm and Support Vector Regression
Xiaoyong Lu, Xiaomeng Geng · 2011
In this paper, the car sales prediction model is established by using Support Vector Regression (SVR) combined with Particles Swarm Optimization algorithm (PSO-SVR). In this model, PSO Algorithm is used to optimize the 3 parameter used in Support Vector Regression. PSO algorithm not only has a strong global search capability, but also solved the problem of over-fitting. Moreover, Mean Absolute Percentage Error(MAPE) is used to measure the error between predict value and actual value. The experimental result shows that the PSO-SVR model is superior to GA-SVR model in the running efficiency and predict accuracy.