Using Machine Learning for the Precise Experimental Modeling of Catastrophe Phenomena: Taking the Establishment of an Experimental Mathematical Model of a Cusp-Type Catastrophe for the Zeeman Catastrophe Machine as an Example

Using Machine Learning for the Precise Experimental Modeling of Catastrophe Phenomena: Taking the Establishment of an Experimental Mathematical Model of a Cusp-Type Catastrophe for the Zeeman Catastrophe Machine as an Example

When catastrophe theory is applied to the experimental modeling of catastrophe phenomena, it is impossible to know in advance the corresponding relationship and mapping form between the parameters of the actual catastrophe mathematical model and the parameters of the canonical catastrophe mathematic...

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Bibliographic Details
Main Authors: Shaonan Zhang, Liangshan Xiong
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Mathematics
Subjects:
catastrophe theory
precise experimental modeling
Zeeman catastrophe machine
machine learning
Online Access:https://www.mdpi.com/2227-7390/13/4/603

Internet

https://www.mdpi.com/2227-7390/13/4/603

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