基于统计分析阈值的航段油耗分段线性估计模型
DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

X738

基金项目:

2021年度天津市教委社会科学重大项目(2021JWZD39);中国民航局安全能力项目(SKZ49420210017)


Piecewise linear estimation model of segment fuel consumption based on statistical analysis threshold
Author:
Affiliation:

Fund Project:

Major social science project of Tianjin Education Commission in 2021 (2021jwzd39); Safety capability project of Civil Aviation Administration of China (skz49420210017)

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    航程油耗的非线性复杂特征为合理、准确判断航空运输过程碳排放量进而有效控碳带来了诸多困难。为此,构建了一种基于统计分析阈值的运输过程航段油耗分段线性估计模型。该模型在飞机运输过程航段油耗高阶多项式表达的基础上,以全航程航段油耗核证重要性指标作为统计分析阈值来设定多项式表达线性化分段的依据,从而兼顾科学计算准确性与碳核证实操合理性。实例分析结果表明了方法的有效性。

    Abstract:

    The nonlinear complex characteristics of voyage fuel consumption bring many difficulties to reasonably and accurately determine carbon emission in the process of air transportation and then effectively control carbon. Therefore, a piecewise linear estimation model of fuel consumption in transportation process based on statistical analysis threshold is constructed. Based on the expression of higher order polynomials of fuel consumption in the process of aircraft transportation, the model establishes the basis of polynomial expression of linear segmentation by threshold of statistical analysis, so as to take into account the accuracy of scientific calculation and the reasonableness of carbon certification practice. The results of example analysis show the effectiveness of the method.

    参考文献
    相似文献
    引证文献
引用本文

刘志,陈静杰. 基于统计分析阈值的航段油耗分段线性估计模型[J]. 科学技术与工程, 2022, 22(23): 10341-10346.
Liu Zhi, Chen Jingjie. Piecewise linear estimation model of segment fuel consumption based on statistical analysis threshold[J]. Science Technology and Engineering,2022,22(23):10341-10346.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2021-12-02
  • 最后修改日期:2022-07-26
  • 录用日期:2022-04-04
  • 在线发布日期: 2022-09-06
  • 出版日期:
×
律回春渐,新元肇启|《科学技术与工程》编辑部恭祝新岁!
亟待确认版面费归属稿件,敬请作者关注