A review on big data based on deep neural network approaches-Reference-Cited by-同舟云学术

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A review on big data based on deep neural network approaches

Published:2023-06-07 Issue:12 Volume:56 Page:14765-14801
ISSN:0269-2821
Container-title:Artificial Intelligence Review
language:en
Short-container-title:Artif Intell Rev

Author:

Rithani M.,Kumar R. Prasanna,Doss Srinath

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Link

https://link.springer.com/content/pdf/10.1007/s10462-023-10512-5.pdf

Reference150 articles.

1. Acharya S, Rai A, Venkatesh S, Ravindranath Chowdary C (2021) A review of transfer learning in deep neural networks. J Big Data 8(1):1–21

2. Ahmad J, Larijani H, Emmanuel R, Mannion M, Javed A, Phillipson M (2017) Energy demand prediction through novel random neural network predictor for large non-domestic buildings. In: Proc. Annu. IEEE Int. Syst. Conf., pp 1–6. https://doi.org/10.1109/SYSCON.2017.7934803

3. Akbal Y, Ünlü KD (2022a) A univariate time series methodology based on sequence-to-sequence learning for short to midterm wind power production. Renew Energy 200:832–844. https://doi.org/10.1016/j.renene.2022.10.055

4. Akbal Y, Ünlü KD (2022b) A deep learning approach to model daily particular matter of Ankara: Key features and forecasting. Int J Environ Sci Technol 19(7):5911–5927. https://doi.org/10.1007/s13762-021-03730-3

5. Alaluf I, Polyak A, Goldberg Y (2021) SparseGAN: Sparsity-promoting generative adversarial networks for compressed sensing MRI. Med Image Anal 71:102036

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