Volume 17, Issue 1 (2015)
JAST 2015, 17(1): 1-10 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Mohaddes S A, Fahimifard S M. Application of Adaptive Neuro-Fuzzy Inference System (ANFIS) in Forecasting Agricultural Products Export Revenues (Case of Iran’s Agriculture Sector). JAST 2015; 17 (1) :1-10
URL: http://jast.modares.ac.ir/article-23-11445-en.html
URL: http://jast.modares.ac.ir/article-23-11445-en.html
1- Agriculture and Natural Resources Research Center of Khorasan Razavi, Mashhad, Islamic Republic of Iran.
2- Khorasan Razavi Chamber of Commerce, Industry, Mines and Agriculture, Mashhad, Islamic Republic of Iran.
2- Khorasan Razavi Chamber of Commerce, Industry, Mines and Agriculture, Mashhad, Islamic Republic of Iran.
Abstract: (7497 Views)
In this study, application of Adaptive Neuro-Fuzzy Inference System (ANFIS) in forecasting three perspectives (1, 2, and 4 years) ahead of Iran’s agricultural products export was compared with ARIMA as the most common econometrics linear forecasting method. For this purpose, Iran’s agricultural products export revenues related to 1959-2010, and forecast performance measures such as R2, MAD, and RMSE were used. Results of the models performance evaluation showed that the forecasted test data related to ANFIS designed architects had more correspondence with the real data in comparison with that of ARIMA forecasted out of sample data. Therefore, the non-linear ANFIS model outperformed the linear ARIMA model for all of the considered perspectives.
Article Type: Research Paper |
Subject:
Agricultural Economics
Received: 2013/05/4 | Accepted: 2014/05/7 | Published: 2015/01/1
Received: 2013/05/4 | Accepted: 2014/05/7 | Published: 2015/01/1
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |