<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper refers to the Lagrangian mathematical model and the Rackwitz-Fiessler transform model in modeling advanced mathematics applications. In this paper, the Lagrangian interpolation method and Rackwitz-Fiessler transform are used to calculate the correlation coefficient efficiently. The purpose of this algorithm is to speed up the process of probabilistic modeling. This paper uses integral probability transformation to characterize the output's uncertainty by the production's joint distribution function. The purpose of this process is to improve the reliability of the calculation. Through the algorithm analysis, it is found that the method is reasonable and efficient.</p>
</abstract>

This paper refers to the Lagrangian mathematical model and the Rackwitz-Fiessler transform model in modeling advanced mathematics applications. In this paper, the Lagrangian interpolation method and Rackwitz-Fiessler transform are used to calculate the correlation coefficient efficiently. The purpose of this algorithm is to speed up the process of probabilistic modeling. This paper uses integral probability transformation to characterize the output's uncertainty by the production's joint distribution function. The purpose of this process is to improve the reliability of the calculation. Through the algorithm analysis, it is found that the method is reasonable and efficient.

Higher Mathematics Teaching Curriculum Model Based on Lagrangian Mathematical Model

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper refers to the Lagrangian mathematical model and the Rackwitz-Fiessler transform model in modeling advanced mathematics applications. In this paper,...

Higher Mathematics Teaching Curriculum Model Based on Lagrangian Mathematical Model

Online veröffentlicht: 06. Juni 2023

Seitenbereich: 229 - 236

Eingereicht: 11. Jan. 2022

Akzeptiert: 30. März 2022

DOI: https://doi.org/10.2478/amns.2022.2.00003

Schlüsselwörter
Lagrangian mathematical model, Rackwitz-Fiessler transform, Advanced mathematics, Mathematical modeling

© 2023 Jianxia Guo, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Higher Mathematics Teaching Curriculum Model Based on Lagrangian Mathematical Model

Online veröffentlicht: 06. Juni 2023

Seitenbereich: 229 - 236

Eingereicht: 11. Jan. 2022

Akzeptiert: 30. März 2022

DOI: https://doi.org/10.2478/amns.2022.2.00003

SchlüsselwörterLagrangian mathematical model, Rackwitz-Fiessler transform, Advanced mathematics, Mathematical modeling

© 2023 Jianxia Guo, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Lagrangian mathematical model, Rackwitz-Fiessler transform, Advanced mathematics, Mathematical modeling