Inflation rate modeling: Adaptive neuro-fuzzy inference system approach and particle swarm optimization algorithm (ANFIS-PSO)

In this paper, modeling was performed using the combination of the ANFIS method and PSO algorithm for the inflation rate in Iran. The data of this article were obtained from the Central Bank of the Islamic Republic of Iran. The raw data are related to the country of the Islamic Republic of Iran and in the period (1986–2018). The purpose of this article is to use the time series data; in the ANFIS system to be trained with the PSO algorithm and using the trained network, a suitable model for production inflation rate be. Inflation is beneficial as an influential variable in economic activity in economic research. Researchers working in macroeconomics, monetary economics, and public sector economics can use the model produced in this paper to analyze inflation formation better. • We are improving modeling quality by combining ANFIS-PSO. • Inflation is widely used in economic analysis. • Inflation rate modeling is a tool for developing anti-inflation programs.