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Self-learning locally-optimal hypertuning using maximum entropy, and comparison of machine learning approaches for estimating fatigue life in composite materials. (arXiv:2210.10783v1 [cs.LG])
cs.LG updates on arXiv.org arxiv.org
Applications of Structural Health Monitoring (SHM) combined with Machine
Learning (ML) techniques enhance real-time performance tracking and increase
structural integrity awareness of civil, aerospace and automotive
infrastructures. This SHM-ML synergy has gained popularity in the last years
thanks to the anticipation of maintenance provided by arising ML algorithms and
their ability of handling large quantities of data and considering their
influence in the problem.
In this paper we develop a novel ML nearest-neighbors-alike algorithm based
on the principle of maximum …
arxiv comparison entropy life machine machine learning materials self-learning