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Modeling, simulation, and prediction of global energy indices: a differential approach
Frontiers in Energy ( IF 3.1 ) Pub Date : 2021-03-18 , DOI: 10.1007/s11708-021-0723-6
Stephen Ndubuisi Nnamchi , Onyinyechi Adanma Nnamchi , Janice Desire Busingye , Maxwell Azubuike Ijomah , Philip Ikechi Obasi

Modeling, simulation, and prediction of global energy indices remain veritable tools for econometric, engineering, analysis, and prediction of energy indices. Thus, this paper differentially modeled, simulated, and non-differentially predicated the global energy indices. The state-of-the-art of the research includes normalization of energy indices, generation of differential rate terms, and regression of rate terms against energy indices to generate coefficients and unexplained terms. On imposition of initial conditions, the solution to the system of linear differential equations was realized in a Matlab environment. There was a strong agreement between the simulated and the field data. The exact solutions are ideal for interpolative prediction of historic data. Furthermore, the simulated data were upgraded for extrapolative prediction of energy indices by introducing an innovative model, which is the synergy of deflated and inflated prediction factors. The innovative model yielded a trendy prediction data for energy consumption, gross domestic product, carbon dioxide emission and human development index. However, the oil price was untrendy, which could be attributed to odd circumstances. Moreover, the sensitivity of the differential rate terms was instrumental in discovering the overwhelming effect of independent indices on the dependent index. Clearly, this paper has accomplished interpolative and extrapolative prediction of energy indices and equally recommends for further investigation of the untrendy nature of oil price.



中文翻译:

全球能源指数的建模,模拟和预测:一种差分方法

全球能源指数的建模,仿真和预测仍然是用于能源计量,工程,分析和预测的可靠工具。因此,本文对全球能源指数进行了差分建模,模拟和非差分预测。该研究的最新水平包括能量指数的标准化,差分速率项的生成以及速率项对能量指数的回归以生成系数和无法解释的项。通过施加初始条件,在Matlab环境中实现了线性微分方程组的解。在模拟数据和现场数据之间有很强的一致性。精确的解决方案是历史数据的插值预测的理想选择。此外,通过引入创新模型,将模拟数据升级为能量指数的外推预测,这是放气和膨胀的预测因子的协同作用。创新的模型产生了关于能源消耗,国内生产总值,二氧化碳排放量和人类发展指数的流行预测数据。但是,石油价格不稳,这可能是由于奇怪的情况造成的。此外,差分速率项的敏感性有助于发现独立索引对相关索引的压倒性影响。显然,本文已经完成了能源指数的内插和外推预测,并同样建议进一步研究石油价格的不稳定性。这是放气和膨胀的预测因子的协同作用。创新的模型产生了关于能源消耗,国内生产总值,二氧化碳排放量和人类发展指数的流行预测数据。但是,石油价格不稳,这可能是由于奇怪的情况造成的。此外,差分速率项的敏感性有助于发现独立索引对相关索引的压倒性影响。显然,本文已经完成了能源指数的内插和外推预测,并同样建议进一步研究石油价格的不稳定性。这是放气和膨胀的预测因子的协同作用。创新的模型产生了关于能源消耗,国内生产总值,二氧化碳排放量和人类发展指数的流行预测数据。但是,石油价格不稳,这可能是由于奇怪的情况造成的。此外,差分速率项的敏感性有助于发现独立索引对相关索引的压倒性影响。显然,本文已经完成了能源指数的内插和外推预测,并同样建议进一步研究石油价格的不稳定性。这可以归因于奇怪的情况。此外,差分速率项的敏感性有助于发现独立索引对相关索引的压倒性影响。显然,本文已经完成了能源指数的内插和外推预测,并同样建议进一步研究石油价格的不稳定性。这可以归因于奇怪的情况。此外,差分速率项的敏感性有助于发现独立索引对相关索引的压倒性影响。显然,本文已经完成了能源指数的内插和外推预测,并同样建议进一步研究石油价格的不稳定性。

更新日期:2021-03-23
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