Forecasting seasonality in prices of potatoes and onions: challenge between geostatistical models, neuro fuzzy approach and Winter method

This paper, we studied the ability of geostatistical models (ordinary kriging (OK) and Inverse distance weighting (IDW)), adaptive neuro-fuzzy inference system (ANFIS) and Winter method for prediction of seasonality in prices of potatoes and onions in Iran over the seasonal period 1986_2001. Results show that the best estimators in order are winter method, ANFIS and geostatistical methods. The results indicate that Winter and ANFIS had powerful results for prediction the prices while geostatistical models were not useful in this respect.

[1]  Alex B. McBratney,et al.  A comparison of prediction methods for the creation of field-extent soil property maps , 2001 .

[2]  Marcus O'Connor,et al.  Artificial neural network models for forecasting and decision making , 1994 .

[3]  C. Granger,et al.  The use of R2 to determine the appropriate transformation of regression variables , 1976 .

[4]  Ken Black,et al.  Business Statistics: Contemporary Decision Making , 1994 .

[5]  James W. Taylor Exponential smoothing with a damped multiplicative trend , 2003 .

[6]  Francisco Cabrera,et al.  Spatial variability of the chemical characteristics of a trace-element-contaminated soil before and after remediation , 2006 .

[7]  Alwyn E. Annels,et al.  Geostatistical Ore-reserve Estimation , 1991 .

[8]  Marc Voltz,et al.  A comparison of kriging, cubic splines and classification for predicting soil properties from sample information , 1990 .

[9]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[10]  G. Metternicht,et al.  Testing the performance of spatial interpolation techniques for mapping soil properties , 2006 .

[12]  Jeffrey G. White,et al.  Spatial variability of Southeastern U.S. Coastal Plain soil physical properties: Implications for site-specific management , 2007 .

[13]  L. Mabit,et al.  Assessment of spatial distribution of fallout radionuclides through geostatistics concept. , 2007, Journal of environmental radioactivity.

[14]  J. Bouma,et al.  Accuracy of spatial interpolation between point data on soil moisture supply capacity, compared with estimates from mapping units , 1982 .

[15]  Robert Haining,et al.  Statistics for spatial data: by Noel Cressie, 1991, John Wiley & Sons, New York, 900 p., ISBN 0-471-84336-9, US $89.95 , 1993 .

[16]  N. Cressie Fitting variogram models by weighted least squares , 1985 .

[17]  M. Sugeno,et al.  Derivation of Fuzzy Control Rules from Human Operator's Control Actions , 1983 .

[18]  Stephen L. Chiu,et al.  Fuzzy Model Identification Based on Cluster Estimation , 1994, J. Intell. Fuzzy Syst..

[19]  D. G. Krige,et al.  Lognormal-de Wijsian geostatistics for ore evaluation , 1978 .

[20]  Hui Zou,et al.  Combining time series models for forecasting , 2004, International Journal of Forecasting.

[21]  Kesten C. Green,et al.  Demand Forecasting: Evidence-Based Methods , 2005 .