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Provedor de dados:  AgEcon
País:  United States
Título:  Forecasting seasonality in prices of potatoes and onions: challenge between geostatistical models, neuro fuzzy approach and Winter method
Autores:  Amiri, Arshia
Bakhshoodeh, Mohamad
Najafi, Bahaeddin
Data:  2011-10-13
Ano:  2011
Palavras-chave:  Price
Geostatistical model
Kiriging
Inverse distance weighting
Winter’s method
Adaptive neuro fuzzy inference system
Potatoes
Onions
Iran
Crop Production/Industries
Demand and Price Analysis
Resumo:  Munich Personal RePEc Archive

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.
Tipo:  Technical Report
Idioma:  Inglês
Identificador:  http://purl.umn.edu/119154
Relação:  Miscellaneous Papers>Miscellaneous Papers
MPRA Paper
34093
Formato:  11
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