Flowcean - Model Learning for Cyber-Physical Systems

• URL: http://arxiv.org/abs/2603.12015v1
• Date: Thu, 12 Mar 2026 14:57:50 GMT
• Title: Flowcean - Model Learning for Cyber-Physical Systems
• Abstract summary: Flowcean is a novel framework designed to automate the generation of models.<n>It focuses on data-driven learning that focuses on modularity and usability.
• Score: 0.3243104097643199
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Effective models of Cyber-Physical Systems (CPS) are crucial for their design and operation. Constructing such models is difficult and time-consuming due to the inherent complexity of CPS. As a result, data-driven model generation using machine learning methods is gaining popularity. In this paper, we present Flowcean, a novel framework designed to automate the generation of models through data-driven learning that focuses on modularity and usability. By offering various learning strategies, data processing methods, and evaluation metrics, our framework provides a comprehensive solution, tailored to CPS scenarios. Flowcean facilitates the integration of diverse learning libraries and tools within a modular and flexible architecture, ensuring adaptability to a wide range of modeling tasks. This streamlines the process of model generation and evaluation, making it more efficient and accessible.

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