ISSN:
2352-4847
Inhalt:
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.
In:
Energy reports, Amsterdam [u.a.] : Elsevier, 2015, 6(2020) vom: Nov., Seite 1608-1618, 2352-4847
In:
volume:6
In:
year:2020
In:
month:11
In:
pages:1608-1618
Sprache:
Englisch
Schlagwort(e):
Aufsatz in Zeitschrift
DOI:
10.1016/j.egyr.2020.05.021
