张量分解在电磁学和能量学中的潜在应用综述

Ismail A. Mageed, Musa Yilmaz, Quichun Zhang, Resat Çelikel, M. Sidhu
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引用次数: 0

摘要

本文对张量分解(TD)方法进行了综述。对于不确定性量化和电磁(EM)求解,我们介绍了它们在代理建模(SM)中的应用。目前的研究讨论是关于这些分解对降低记忆的重大影响。此外,本文还对TDs在能源研究中的重要作用进行了综述。后一篇综述巩固了进一步利用td推进研究工作的更基本的动机和见解。最后给出了结论和未来的发展方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A review of potential applications of Tensor Decompositions to Electromagnetics and energy works
The approaches for tensor decomposition (TD) are reviewed in this study. For uncertainty quantification and electromagnetic (EM) solvers, we cover their applications to surrogate modeling (SM). The current study Discussion is undertaken regarding the significant impact of these decompositions on lowering memory. Additionally, the influential role of TDs in energy research is thoroughly reviewed. The latter review consolidates more foundational motivations and insights into further employment of TDs to advance research works. Conclusions and future directions are given.
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