See the published version of this article at Optical and Quantum Electronics.
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Research Article
Joachim Piprek
NUSOD Institute LLC
Corresponding Author
ORCiD: https://orcid.org/0000-0002-4002-1629
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This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Optical and Quantum Electronics.
Numerical simulation and machine learning represent opposite approaches to computational analysis of the real world, deductive vs. inductive. However, both methods suffer from various uncertainties and even their combination often fails to link theory and reality. Focusing on GaN-based light-emitting diode (LED) design optimization, this paper evaluates examples of simulation-based machine learning from a physics point of view. Strategies are suggested for achieving more realistic predictions.
Keywords
machine learning, deep learning, neural networks, artificial intelligence, numerical simulation, design optimization, light-emitting diode
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This preprint is under consideration at Optical and Quantum Electronics. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Joachim Piprek
NUSOD Institute LLC
Corresponding Author
ORCiD: https://orcid.org/0000-0002-4002-1629
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 1
Posted 04 Mar, 2021
Published
On 24 Mar, 2021
No community comments so far
Editor assigned
On 28 Feb, 2021
First submitted
On 10 Jan, 2021
Editorial decision: Accept
On 05 Jan, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Optical and Quantum Electronics.
Numerical simulation and machine learning represent opposite approaches to computational analysis of the real world, deductive vs. inductive. However, both methods suffer from various uncertainties and even their combination often fails to link theory and reality. Focusing on GaN-based light-emitting diode (LED) design optimization, this paper evaluates examples of simulation-based machine learning from a physics point of view. Strategies are suggested for achieving more realistic predictions.
Figure 1
Figure 2
Figure 3
Figure 4
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