Neural Networks and Classical Algorithms in Inverse Problems of Anomalous Diffusion Full article
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Science and Artificial Intelligence Conference, S.A.I.ence 14-15 Nov 2020 , Новосибирск |
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| Source | Proceedings - 2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020 Compilation, IEEE. 2020. 68 c. |
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| Output data | Year: 2020, Article number : 9303217, Pages count : 4 DOI: 10.1109/S.A.I.ence50533.2020.9303217 | ||||||
| Tags | anomalous diffusion; artificial neural networks; inverse problems; numerical methods | ||||||
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Abstract:
The paper develops a new numerical method for the solution of the inverse problems. This method can be classified as a predictor-corrector method, in which the artificial neural network plays the role of a predictor, and the gradient method plays the role of a corrector. We apply this method to inverse anomalous diffusion problem and show its statistical efficiency. © 2020 IEEE.
Cite:
Dedok V.A.
, Bugueva T.V.
Neural Networks and Classical Algorithms in Inverse Problems of Anomalous Diffusion
In compilation Proceedings - 2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020. – IEEE., 2020. – C.9-12. DOI: 10.1109/S.A.I.ence50533.2020.9303217 Scopus OpenAlex
Neural Networks and Classical Algorithms in Inverse Problems of Anomalous Diffusion
In compilation Proceedings - 2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020. – IEEE., 2020. – C.9-12. DOI: 10.1109/S.A.I.ence50533.2020.9303217 Scopus OpenAlex
Identifiers:
| Scopus: | 2-s2.0-85099601360 |
| OpenAlex: | W3114258388 |