A new GEP algorithm and its applications in vegetable price forecasting modeling problems

Abstract

In this paper, a new Gene Expression Programming (GEP) algorithm is proposed, which increase “inverted series” and “extract” operator. The new algorithm can effectively increase the rate of utilization of genes, with convergence speed and solution precision is higher. Taking the Chinese vegetables price change trend of mooli, scallion as example, and discuss the way to solve the forecasting modeling problem by adopting GEP. The experimental results show that the new GEP Algorithm can not only increase the diversity of population but overcome the shortage of primitive GEP. In addition, it can improve convergence accuracy compared to original GEP.