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首页> 外文会议>IEEE International Conference on Grey Systems and Intelligent Services >Predict China's per capita GDP based on ending-point optimized discrete grey (1, 1) model
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Predict China's per capita GDP based on ending-point optimized discrete grey (1, 1) model

机译：基于终点优化离散灰色（1，1）模型预测中国人均GDP

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摘要

In this paper, in view of the disadvantages of traditional discrete GM (1, 1) model, we propose the ending-point optimized discrete grey (1, 1) model (EODGM(1,1)) to improve prediction accuracy and give the concrete calculation formula. The novel model assumes that the sequence start iteration from the optimized ending point. We can get optimum initial iteration point by using optimization algorithm proposed in this paper. Because the ending point stands for the latest information, so the EODGM(1,1) is accord with the new information priority principle. We use the data of China's per capita gross domestic product (GDP) from 2001 to 2009 as an example, and the results show that the simulation accuracy of the EODGM(1,1) is superior to the traditional discrete GM (1,1) and ending-point fixed discrete grey model (EDFGM(1,1)). Furthermore, the one step prediction accuracy and two step prediction accuracy has more obvious advantages. The results show that this novel model is effective and applicable.
机译：鉴于传统离散GM（1，1）模型的缺点，我们提出了终点优化离散灰度（1，1）模型（EODGM（1,1））以提高预测精度并给出具体计算公式。新模型假设序列从优化的终点开始迭代。利用本文提出的优化算法可以获得最优的初始迭代点。因为终点代表最新信息，所以EODGM（1,1）符合新信息优先级原则。以2001年至2009年中国人均国内生产总值的数据为例，结果表明，EODGM（1,1）的模拟精度优于传统的离散GM（1,1）和终点固定离散灰色模型（EDFGM（1,1））。此外，一步预测精度和两步预测精度具有更明显的优点。结果表明，该模型是有效的和适用的。

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