<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

Publié en ligne: 06 juin 2023

Pages: 229 - 236

Reçu: 11 janv. 2022

Accepté: 30 mars 2022

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

Mots clés
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

Publié en ligne: 06 juin 2023

Pages: 229 - 236

Reçu: 11 janv. 2022

Accepté: 30 mars 2022

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

Mots clésLagrangian 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.

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