Modellreduzierung
Modellreduzierung, also known as model reduction, is a technique used in various fields, including engineering, physics, and data science, to simplify complex models while preserving their essential characteristics. This process is particularly valuable when dealing with large-scale systems that are computationally expensive to simulate or analyze.
The primary goal of Modellreduzierung is to create a reduced-order model (ROM) that approximates the behavior
Several methods exist for performing Modellreduzierung, including Proper Orthogonal Decomposition (POD), Balanced Truncation, and Krylov Subspace
One of the key challenges in Modellreduzierung is ensuring that the reduced model accurately represents the
In summary, Modellreduzierung is a powerful tool for simplifying complex models, enabling efficient analysis and control