DocumentCode
2970745
Title
Using an artificial neural network to forecast the market share of Thai rice
Author
Apichottanakul, A. ; Piewthongngam, K. ; Pathumnakul, S.
Author_Institution
Grad. Sch., Khon Kaen Univ., Khon Kaen, Thailand
fYear
2009
fDate
8-11 Dec. 2009
Firstpage
665
Lastpage
668
Abstract
In this paper, the artificial neural networks (ANN) is used to estimate the market share of Thai rice in the global market. Two models are formulated under two assumptions. First, the market share depending on exporting prices of rice of Thailand, Vietnam, India, USA, Pakistan, China. Second, only the export prices of rice from Thailand, Vietnam, USA, and China are considered. The export prices are used as input parameters, while the market share of Thai´s rice in the global market is the only output parameter of the models. Annual data from 1980 to 2005 are gathered from United States Department of Agriculture (USDA) and Food and Agriculture Organization of the United Nations (FAO). The study showed that the second model provide more promising results with the minimum mean absolute percent error (MAPE) of 4.69% and the average MAPE of 10.92%.
Keywords
agricultural products; demand forecasting; food products; globalisation; neural nets; pricing; Thai rice; artificial neural network; export price; global market; market share; Agricultural products; Artificial neural networks; Demand forecasting; Economic forecasting; Globalization; Industrial relations; Production; Supply chains; US Department of Agriculture; Uncertainty; Neural networks; back propagation; demand for rice; market share;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-4869-2
Electronic_ISBN
978-1-4244-4870-8
Type
conf
DOI
10.1109/IEEM.2009.5373247
Filename
5373247
Link To Document