首页|Findings from Gdansk University of Technology Provides New Data on Machine Learn ing (Rapid Surrogate-aided Multicriterial Optimization of Compact Microwave Pass ives Employing Machine Learning and Anns)
Findings from Gdansk University of Technology Provides New Data on Machine Learn ing (Rapid Surrogate-aided Multicriterial Optimization of Compact Microwave Pass ives Employing Machine Learning and Anns)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news reporting originating from Gdansk,Poland,b y NewsRx correspondents,research stated,"This article introduces an innovative method for achieving low-cost and reliable multiobjective optimization (MOO) of microwave passive circuits. The technique capitalizes on the attributes of surr ogate models,specifically artificial neural networks (ANNs),and multiresolutio n electromagnetic (EM) analysis." Financial support for this research came from Icelandic Center for Research (RAN NIS). Our news editors obtained a quote from the research from the Gdansk University o f Technology,"We integrate the search process into a machine learning (ML) fram ework,where each iteration produces multiple infill points selected from the pr esent representation of the Pareto set. This collection is formed by optimizing the ANN metamodel by means of a multiobjective evolutionary algorithm (MOEA). Th e procedure concludes upon convergence,defined as a significant similarity betw een the sets of nondominated solutions acquired through consecutive iterations. Performing the majority of iterations at the low-fidelity EM simulation level en ables additional computational savings. Our methodology has been showcased using two microstrip circuits."
GdanskPolandEuropeCyborgsEmergin g TechnologiesMachine LearningGdansk University of Technology
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