Findings from University College Dublin Provides New Data about Machine Learning (Incremental Learning of Parameter Spaces In Machine-learning Based Reliability Analysis)
Findings from University College Dublin Provides New Data about Machine Learning (Incremental Learning of Parameter Spaces In Machine-learning Based Reliability Analysis)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting from Dublin, Ireland, by Ne wsRx journalists, research stated, “Significant advances in machine -learning ba sed reliability analysis occurred recently. These allowed it to be performed wit h high effectiveness.” The news correspondents obtained a quote from the research from University Colle ge Dublin, “However, in most applications the problem of reliability is treated within a closed setup, and if a change in the problem is needed a posteriori , t he reliability needs to be re -assessed, which often results in an inefficient u sage of resources. In this context, the present work argues that established rel iability knowledge can inform the assessment of a similar problem under paramete r changes. It uses incremental learning in an augmented space to solve a reliabi lity analysis with dependence on parameter variations. It is shown that only the points that swap their classification are of interest to reassess reliability, which has large synergy with machine learning and classification. A learning app roach that uses this synergy is proposed to search for the points that are under a class change. It is tested in four examples and uses adaptive kriging. The re sults show that with only few additional evaluations of the true function it is possible to accurately (at <1% loss in accura cy) assess the reliability for a relatively complex problem experiencing changes in its parameters.”
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Dublin/Ireland/Europe/Cyborgs/Emergi ng Technologies/Machine Learning/University College Dublin
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