Titlebook: Machine Learning for Cyber-Physical Systems; Selected papers from Oliver Niggemann,Jürgen Beyerer,Christian Kühnert Conference proceedings‘

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,A Digital Twin Design for?Conveyor Belts Predictive Maintenance,sults that can be used reliably in terms of data quality. One of the ways to obtain data from the system is through the development of a digital twin. Therefore, a digital twin design might be of key value for the predictive maintenance of systems enabling the simulation of the system’s performance,

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,Augmenting Explainable Data-Driven Models in?Energy Systems: A Python Framework for?Feature Engineeh as linear regression, neural networks or decision-tree based methods are applied. While these methods do not require domain knowledge, they are sensitive to data quality. Therefore, improving data quality in a dataset is beneficial for creating machine learning-based models. The improvement of dat

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Conference proceedings‘‘‘‘‘‘‘‘ 2024, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments..This is an open access book..

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