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Application of a new grey prediction model and grey average weakening buffer operator to forecast China’s shale gas output

机译：一种新的灰色预测模型和灰色平均弱化缓冲器操作员在中国页岩气输出中的应用

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摘要

Scientifically and accurately forecasting of future shale gas output tends is very important in making energy policies, especially for China whose historical data of shale gas output is very limited. The existing grey shale gas output prediction model does not perform well in prediction due to its defects. To overcome these shortcoming, this paper, based on the principle of “new information priority”, combined with the contradiction between model prediction results and qualitative data analysis conclusions, designs a grey prediction model combining new initial conditions and original data reprocessing. Then the new model’s accumulative order is optimized by fraction accumulation generation operation and its properties is discussed. Finally, the new model is used to simulate and forecast shale gas output in China from 2012 to 2018 and compared it with the existing shale gas prediction model. The comparison results show that the new model reduces by 84.34%, 68.96% and 75.60% of the mean relative simulation percentage error (MRSPE), mean relative prediction percentage error (MRPPE) and comprehensive mean relative percentage error (CMPPE) respectively. This paper not only has theoretical innovations but also provides a good mathematical method for predicting shale gas output.
机译：科学和准确的预测未来的页岩气输出趋于在制定能源政策方面非常重要，特别是对于中国的历史数据输出的历史数据非常有限。由于其缺陷，现有的灰色页岩气体输出预测模型在预测中不得良好。为了克服这些缺点，本文基于“新信息优先权”的原则，结合模型预测结果与定性数据分析结论之间的矛盾，设计了新的初始条件和原始数据再处理的灰色预测模型。然后，新模型的累积顺序通过分数累积产生操作进行了优化，并且讨论了其性质。最后，新型模型用于从2012年到2018年在中国模拟和预测页岩气产量，并将其与现有的页岩气预测模型进行比较。比较结果表明，新模型的平均相对模拟百分比误差（MRSPE），平均相对预测百分比误差（MRPPE）和综合平均相对百分比误差（CMPPE）减少了84.34％，68.96％和75.60％。本文不仅具有理论创新，还提供了一种预测页岩气输出的良好数学方法。

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