Výsledky vyhledávání - "Clarkson, A. R."

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Active learning for regression in engineering populations: A risk-informed approach

Autor: Clarkson, Daniel R., Bull, Lawrence A., Wickramarachchi, Chandula T., Cross, Elizabeth J., Rogers, Timothy J., Worden, Keith, Dervilis, Nikolaos, Hughes, Aidan J.

Regression is a fundamental prediction task common in data-centric engineering applications that involves learning mappings between continuous variables. In many engineering applications (e.g.\ structural health monitoring), feature-label pairs used

Externí odkaz: http://arxiv.org/abs/2409.04328

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Sharing Information Between Machine Tools to Improve Surface Finish Forecasting

Autor: Clarkson, Daniel R., Bull, Lawrence A., Dardeno, Tina A., Wickramarachchi, Chandula T., Cross, Elizabeth J., Rogers, Timothy J., Worden, Keith, Dervilis, Nikolaos, Hughes, Aidan J.

At present, most surface-quality prediction methods can only perform single-task prediction which results in under-utilised datasets, repetitive work and increased experimental costs. To counter this, the authors propose a Bayesian hierarchical model

Externí odkaz: http://arxiv.org/abs/2310.05807

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