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Finsler Geometry for Two‐Parameter Weibull Distribution Function
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To construct the geometry in nonflat spaces in order to understand nature has great importance in terms of applied science. Finsler geometry allows accurate modeling and describing ability for asymmetric structures in this application area. In this paper, two‐dimensional Finsler space metric function is obtained for Weibull distribution which is used in many applications in this area such as wind speed modeling. The metric definition for two‐parameter Weibull probability density function which has shape (k) and scale (c) parameters in two‐dimensional Finsler space is realized using a different approach by Finsler geometry. In addition, new probability and cumulative probability density functions based on Finsler geometry are proposed which can be used in many real world applications. For future studies, it is aimed at proposing more accurate models by using this novel approach than the models which have two‐parameter Weibull probability density function, especially used for determination of wind energy potential of a region.
Title: Finsler Geometry for Two‐Parameter Weibull Distribution Function
Description:
To construct the geometry in nonflat spaces in order to understand nature has great importance in terms of applied science.
Finsler geometry allows accurate modeling and describing ability for asymmetric structures in this application area.
In this paper, two‐dimensional Finsler space metric function is obtained for Weibull distribution which is used in many applications in this area such as wind speed modeling.
The metric definition for two‐parameter Weibull probability density function which has shape (k) and scale (c) parameters in two‐dimensional Finsler space is realized using a different approach by Finsler geometry.
In addition, new probability and cumulative probability density functions based on Finsler geometry are proposed which can be used in many real world applications.
For future studies, it is aimed at proposing more accurate models by using this novel approach than the models which have two‐parameter Weibull probability density function, especially used for determination of wind energy potential of a region.
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