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Using an artificial neural network to forecast the market share of Thai rice

机译:使用人工神经网络预测泰国大米的市场份额

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摘要

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%.
机译:本文使用人工神经网络(ANN)来估计泰国大米在全球市场中的市场份额。在两个假设下制定了两个模型。首先,市场份额取决于泰国,越南,印度,美国,巴基斯坦,中国的大米出口价格。其次,仅考虑泰国,越南,美国和中国的大米出口价格。出口价格用作输入参数,而泰国大米在全球市场中的市场份额是模型的唯一输出参数。 1980年至2005年的年度数据来自美国农业部(USDA)和联合国粮食及农业组织(FAO)。研究表明,第二个模型提供了更令人满意的结果,最小平均绝对百分比误差(MAPE)为4.69%,平均MAPE为10.92%。

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