2023
DOI: 10.1016/j.matchemphys.2023.128180
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Multiband Metamaterial absorber with absorption prediction by assisted machine learning

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Cited by 25 publications
(6 citation statements)
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References 37 publications
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“…This can be a suitable solution for regression problems with inadequate data because it is less prone to overfitting than single decision trees [38] [39]. Extra trees are a random forest variant that employs a more randomized technique to train individual trees [40]. This has the potential to improve forecast accuracy, particularly in high-dimensional datasets [6] [41].…”
Section: B Bagging-based Ensemble Modelsmentioning
confidence: 99%
“…This can be a suitable solution for regression problems with inadequate data because it is less prone to overfitting than single decision trees [38] [39]. Extra trees are a random forest variant that employs a more randomized technique to train individual trees [40]. This has the potential to improve forecast accuracy, particularly in high-dimensional datasets [6] [41].…”
Section: B Bagging-based Ensemble Modelsmentioning
confidence: 99%
“…Due to the longer wavelengths of terahertz waves, traditional optical devices 6 often tend to be bulky and complex. However, metasurfaces enable compact and integrated designs, 7 9 simplifying terahertz device structure and fabrication process.…”
Section: Introductionmentioning
confidence: 99%
“…10 Compared with the traditional absorber, the absorber based on metasurface has the characteristics of strong absorption, thin thickness, and light weight. Since Landy et al 11 designed a metasurface-based open ring perfect absorber in 2008, various types of absorbers have come into being, such as narrowband absorption, 12 broadband absorption, 13 and multiband absorption. 14 However, with the development of metasurfaces in recent years, a new problem has arisen: once the metamaterial is designed, its performance cannot be changed, and it is easy to waste resources.…”
Section: Introductionmentioning
confidence: 99%