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Forecasting China's oil consumption: A comparison of novel nonlinear-dynamic grey model (GM), linear GM, nonlinear GM and metabolism GM

机译:预测中国的石油消费:新型非线性-动态灰色模型(GM),线性GM,非线性GM和新陈代谢GM的比较

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摘要

To more accurate forecast China's oil consumption, the major driving force of global new added oil demand, a new nonlinear-dynamic grey model is developed, namely NMGM (1, 1, alpha). The proposed NMGM (1, 1, alpha) upgrades the nonlinear grey model (GM) from stationary to dynamic model through effectively integrating nonlinear forecasting technique and the biological metabolism idea. The proposed NMGM (1,1, alpha), and other three existing grey models (linear GM (1,1), nonlinear GM (1,1, alpha), metabolism GM (1,1)) are run respectively to simulate and forecast Chinese oil consumption from 1990 to 2026. The simulation results show that our proposed NMGM (1, 1, alpha) are higher accurate than the other three models. In addition to better forecast energy consumption, the proposed NMGM (1, 1, alpha) also can be used to forecast in other fields. The modeling results based on the NMGM (1, 1, a) show that China oil consumption in the next decade (2017-2026) will be increased by 51%. The better forecasting Chinese oil consumption by using the proposed model can provide useful information for the researchers, policymakers and others stakeholders in Chinese and global oil market. (C) 2019 Elsevier Ltd. All rights reserved.
机译:为了更准确地预测中国的石油消耗,这是全球新增石油需求的主要驱动力,开发了一种新的非线性动态灰色模型,即NMGM(1,1,alpha)。拟议的NMGM(1,1,alpha)通过将非线性预测技术和生物代谢思想有效整合,将非线性灰色模型(GM)从平稳模型升级为动态模型。分别运行建议的NMGM(1,1,alpha)和其他三个现有的灰色模型(线性GM(1,1),非线性GM(1,1,alpha),新陈代谢GM(1,1))来模拟和预测了1990年至2026年中国的油耗。模拟结果表明,我们提出的NMGM(1,1,alpha)比其他三个模型的准确性更高。除了可以更好地预测能耗之外,建议的NMGM(1、1,alpha)也可以用于其他领域的预测。基于NMGM(1,1,a)的建模结果表明,未来十年(2017-2026)中国的石油消耗量将增加51%。通过使用建议的模型更好地预测中国的石油消耗量,可以为研究人员,政策制定者以及中国和全球石油市场的其他利益相关者提供有用的信息。 (C)2019 Elsevier Ltd.保留所有权利。

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