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A Survey of Selected Grey Forecasting Models with Application to Medical Tourism Forecasting

机译:灰色预测模型的研究及其在医疗旅游预测中的应用

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This paper examines the predictive capacity of two Grey Systems Forecasting models. The original Grey GM(1,1) Forecasting model, introduced by Deng [1] [2] together with an improved Grey GM(1,1) model proposed by Ji et al . [3] are used to forecast medical tourism demand for Bermuda. The paper also introduces a quasi-optimization method for the optimization of the alpha (weight) parameter. Five steps ahead out-of-sample forecasts are produced after estimating the models using four data points. The results indicate that the optimization of the alpha parameter substantially improves the predictive accuracy of the models; reducing the five steps ahead out-of-sample Mean Absolute Percentage Error from roughly 7% to roughly 3.80% across the two models. Largely, the forecasting approaches demonstrate significant potential for use as an alternative to the traditional forecasting methods in circum stances where substantial amounts of high-quality data are not available.
机译:本文研究了两种灰色系统预测模型的预测能力。 Deng [1] [2]提出的原始灰色GM(1,1)预测模型,以及Ji 等人提出的改进的Gray GM(1,1)模型。 [3]用于预测百慕大的医疗旅游需求。本文还介绍了一种用于优化alpha(权重)参数的准优化方法。使用四个数据点估算模型后,将提前五个步骤进行样本外预测。结果表明,阿尔法参数的优化大大提高了模型的预测精度。将两个模型的样本外平均绝对百分比误差的五个步骤从大约7%降低到大约3.80%。在很大程度上,在无法获得大量高质量数据的情况下,预测方法显示出巨大的潜力,可以替代传统的预测方法。

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