Prediction of Amount of Imports Based on Adaptive Neuro-Fuzzy Inference System

Abstract

In this paper, Adaptive network-based fuzzy inference system (ANFIS) was proposed to develop a predictive model for amount of imports. Aggregate import demand function was employed to select input variables. According to aggregate import demand function, the ANFIS model with five input variables and one output variable was built. To show ANFIS model has better ability than some other conventional statistical methods in predicting economics problems, the ANFIS model results were compared with ARIMA model results. The verification of the proposed model was achieved through wave characteristics time series plots and scatter diagrams. The experimental results show that the ANFIS has higher prediction accuracy than some other conventional statistical methods.