An intelligence parameter classification approach for energy storage and natural convection and heat transfer of nano-encapsulated phase change material: Deep neural networks-Reference-Cited by-同舟云学术

An intelligence parameter classification approach for energy storage and natural convection and heat transfer of nano-encapsulated phase change material: Deep neural networks

Published:2023-07-03 Issue:27 Volume:35 Page:19719-19727
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Ghalambaz Mohammad^ORCID,Edalatifar Mohammad,Moradi Maryamnegari Sara^ORCID,Sheremet Mikhail

Funder

Tomsk State University Development Programme

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-023-08708-5.pdf

Reference36 articles.

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4. Altunay FM, Pazarlıoğlu HK, Gürdal M, Tekir M, Arslan K, Gedik E (2022) Thermal performance of Fe3O4/water nanofluid flow in a newly designed dimpled tube under the influence of non-uniform magnetic field. Int J Therm Sci 179:107651

5. Nada SA, El-Zoheiry RM, Elsharnoby M, Osman OS (2022) Enhancing the thermal performance of different flow configuration minichannel heat sink using Al2O3 and CuO-water nanofluids for electronic cooling: an experimental assessment. Int J Therm Sci 181:107767

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