Automatic differentiation for electromagnetic models used in optimization
作者： P. Enciu , F. Wurtz , L. Gerbaud , B. Delinchant
DOI: 10.1108/03321640910969557
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摘要: Purpose – The purpose of this paper is to illustrate automatic differentiation (AD) as a new technology for the device sizing in electromagnetism by using gradient constrained optimization. Component architecture design engineering systems (CADES) framework, previously described, presented here with extended features.Design/methodology/approach subject further usage optimization AD (also named algorithmic differentiation) which powerful technique that computes derivatives functions described computer programs programming language like C/C++, FORTRAN.Findings Indeed, analytical modeling well suited regarding procedure, but complex devices needs sometimes numerical formulations. This then reviews concepts implemented CADES aim manage interactions and inside gradient‐based procedure. Finally, shows has no limit input prog...
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