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Open AccessArticle

A Surrogate Model Based on Artificial Neural Network for RF Radiation Modelling with High-Dimensional Data

1
Chaire C2M, LTCI, Télécom Paris, 19 Place Marguerite Perey, 91120 Palaiseau, France
2
Department of Electronics and Telecommunications, Politecnico di Torino, IT-10129 Turin, Italy
3
IMT Atlantique/Lab-STICC UMR CNRS 6285, Technopole Brest Iroise-CS83818-29238, 29238 Brest CEDEX 03, France
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(7), 2586; https://doi.org/10.3390/ijerph17072586
Received: 4 March 2020 / Revised: 27 March 2020 / Accepted: 2 April 2020 / Published: 9 April 2020
This paper focuses on quantifying the uncertainty in the specific absorption rate values of the brain induced by the uncertain positions of the electroencephalography electrodes placed on the patient’s scalp. To avoid running a large number of simulations, an artificial neural network architecture for uncertainty quantification involving high-dimensional data is proposed in this paper. The proposed method is demonstrated to be an attractive alternative to conventional uncertainty quantification methods because of its considerable advantage in the computational expense and speed. View Full-Text
Keywords: artificial neural networks; uncertainty quantification; specific absorption rate artificial neural networks; uncertainty quantification; specific absorption rate
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MDPI and ACS Style

Cheng, X.; Henry, C.; Andriulli, F.P.; Person, C.; Wiart, J. A Surrogate Model Based on Artificial Neural Network for RF Radiation Modelling with High-Dimensional Data. Int. J. Environ. Res. Public Health 2020, 17, 2586. https://doi.org/10.3390/ijerph17072586

AMA Style

Cheng X, Henry C, Andriulli FP, Person C, Wiart J. A Surrogate Model Based on Artificial Neural Network for RF Radiation Modelling with High-Dimensional Data. International Journal of Environmental Research and Public Health. 2020; 17(7):2586. https://doi.org/10.3390/ijerph17072586

Chicago/Turabian Style

Cheng, Xi; Henry, Clément; Andriulli, Francesco P.; Person, Christian; Wiart, Joe. 2020. "A Surrogate Model Based on Artificial Neural Network for RF Radiation Modelling with High-Dimensional Data" Int. J. Environ. Res. Public Health 17, no. 7: 2586. https://doi.org/10.3390/ijerph17072586

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