Machine-Learning Aided Multiobjective Optimization of Electric Machines— Geometric-Feasibility and Enhanced Regression Models

This article deals with the optimization of electrical machines by means of artificial neural network (ANN)-based classification and regression models. Geometrically (or otherwise) unfeasible designs are detected with high accuracy during the optimization process by means of an ad hoc classification...

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Veröffentlicht in:	IEEE journal of emerging and selected topics in industrial electronics (Print) 2023-07, Vol.4 (3), p.844-854
Hauptverfasser:	Pop, Adrian-Cornel, Cai, Zhaofeng, Gyselinck, Johan J. C.
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Classification Design optimization Finite element method Machine learning Multiple objective analysis Performance prediction Permanent magnets Regression models Synchronous machines Training
Online-Zugang:	Volltext
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