A Novel Methodology for Forecasting Business Cycles Using ARIMA and Neural Network with Weighted Fuzzy Membership Functions

A Novel Methodology for Forecasting Business Cycles Using ARIMA and Neural Network with Weighted Fuzzy Membership Functions

Economic forecasting is crucial since it benefits many different parties, such as governments, businesses, investors, and the general public. This paper presents a novel methodology for forecasting business cycles using an autoregressive integrated moving average (ARIMA), a popular linear model in t...

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Bibliographic Details
Main Authors: Soo H. Chai, Joon S. Lim, Heejin Yoon, Bohyun Wang
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Axioms
Subjects:
time series prediction
neural fuzzy networks
autoregressive integrated moving average
NEWFM
gross domestic product (GDP)
Online Access:https://www.mdpi.com/2075-1680/13/1/56

Internet

https://www.mdpi.com/2075-1680/13/1/56

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