Subscribe Now Subscribe Today
Science Alert
 
FOLLOW US:     Facebook     Twitter
Blue
   
Curve Top
Journal of Artificial Intelligence
  Year: 2009 | Volume: 2 | Issue: 2 | Page No.: 65-72
DOI: 10.3923/jai.2009.65.72
Application of ANFIS to Agricultural Economic Variables Forecasting Case Study: Poultry Retail Price
S.M. Fahimifard, M. Salarpour, M. Sabouhi and S. Shirzady

Abstract:
It is well documented that many economic time series observations are nonlinear and nonlinear models estimated by various methods can fit a data base much better than linear models. Beside they can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems and once trained can perform prediction and generalization at high speed. Therefore, in this study, the utilization of Adaptive Neuro Fuzzy Inference System (ANFIS) as a nonlinear model and Auto-Regressive Integrated Moving Average (ARIMA) model as a linear model are compared to agricultural economic variables time series forecasting. As a case study the three horizons (1, 2 and 4 week ahead) of Iran’s poultry retail price are forecasted using the two mentioned models. The results of using the three forecast evaluation criteria state that, ANFIS model outperforms ARIMA model in all three horizons. And consequently the effective role of ANFIS model to improve the Iran’s poultry retail price forecasting accuracy can’t be denied.
PDF Fulltext XML References Citation Report Citation
 RELATED ARTICLES:
  •    Modeling Energy Use in Dairy Cattle Farms by Applying Multi-Layered Adaptive Neuro-Fuzzy Inference System (MLANFIS)
  •    Application of NNARX to Agricultural Economic Variables Forecasting
How to cite this article:

S.M. Fahimifard, M. Salarpour, M. Sabouhi and S. Shirzady, 2009. Application of ANFIS to Agricultural Economic Variables Forecasting Case Study: Poultry Retail Price. Journal of Artificial Intelligence, 2: 65-72.

DOI: 10.3923/jai.2009.65.72

URL: https://scialert.net/abstract/?doi=jai.2009.65.72

COMMENTS
26 July, 2009
Hamed:
Good job and congratulations.
 
COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 
 
 

       

       

Curve Bottom