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A Survey on Algorithms for Big Data Analysis in Electromagnetics Scattering Problems

Authors:
Christian O. Díaz-Cáez
Chunmei Liu

Keywords: Big Data; Computational Electromagnetics (CEM); Method of Moments (MoM); Fast Algorithms, Multilevel Fast Multipole Algorithm (MLFMA)

Abstract:
Computational Electromagnetics is a discipline that deals with the processing and modeling of multi-physics and electromagnetic problems. Thanks to the advent of computers and numerical methods, engineers today can develop algorithms and software to solve Maxwell’s equations numerically. The electromagnetic scattering problem leads to a very large system of equations with millions or even billions of unknowns; traditional data analysis methods are oftentimes not efficient enough to handle the problem due to data volume. The field of Big Data has emerged from the need to process a massive amount of data and is a research area that facilitates the complex work of extremely large data sizes. Fast algorithms can be developed to efficiently manage the Big Data approach to support areas of science and engineering. In this paper, we explore an application of Big Data and algorithms in computational electromagnetics scattering problems.

Pages: 1 to 6

Copyright: Copyright (c) IARIA, 2021

Publication date: May 30, 2021

Published in: conference

ISSN: 2308-4332

ISBN: 978-1-61208-857-0

Location: Valencia, Spain

Dates: from May 30, 2021 to June 3, 2021