المؤلفون: Farahbod, S., Niknam, T., Mohammadi, M., Aghaei, J., Shojaeiyan, S.

المصدر: IEEE Access Access, IEEE. 10:47063-47075 2022

المؤلفون: Li, L., Fang, Y., Wu, J., Wang, J., Ge, Y.

المصدر: IEEE Transactions on Neural Networks and Learning Systems IEEE Trans. Neural Netw. Learning Syst. Neural Networks and Learning Systems, IEEE Transactions on. 32(9):4217-4230 Sep, 2021

المؤلفون: Kazemivash, Behnam, Calhoun, Vince D.

المصدر: 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE) BIBE Bioinformatics and Bioengineering (BIBE), 2020 IEEE 20th International Conference on. :1071-1076 Oct, 2020

Relation: 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE)

المؤلفون: Li, Lianfa, Fang, Ying, Wu, Jun, Wang, Jinfeng, Ge, Yong

المصدر: IEEE Transactions on Neural Networks and Learning Systems. 32(9)

مصطلحات موضوعية: Information and Computing Sciences, Machine Learning, Bioengineering, Bias, deep learning, encoder-decoder, full residual deep network, non-linear regression, prediction of satellite aerosol optical depth (AOD) and PM2.5, spatiotemporal modeling, Artificial Intelligence & Image Processing, Artificial intelligence

وصف الملف: application/pdf

URL الوصول: https://escholarship.org/uc/item/5bg6p240

المؤلفون: Solmaz Farahbod, Taher Niknam, Mohammad Mohammadi, Jamshid Aghaei, Sattar Shojaeiyan

المصدر: IEEE Access, Vol 10, Pp 47063-47075 (2022)

مصطلحات موضوعية: Wind speed prediction, probability density function (PDF), residual deep network, modified kernel density estimation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/9765965/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/a26105c7a4de49bdb9e54881023141ba

المؤلفون: Lianfa Li

المصدر: Remote Sensing, Vol 13, Iss 12, p 2324 (2021)

مصطلحات موضوعية: aerosol optical depth, ground aerosol coefficient, simulation, adaptive full residual deep network, mainland China, reliability, Science

وصف الملف: electronic resource

Relation: https://www.mdpi.com/2072-4292/13/12/2324; https://doaj.org/toc/2072-4292

URL الوصول: https://doaj.org/article/78097184a95a42c3b0b4f27cdd26b96b

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المؤلفون: Jinfeng Wang, Jun Wu, Ying Fang, Lianfa Li, Yong Ge

المصدر: IEEE transactions on neural networks and learning systems, vol 32, iss 9
IEEE Trans Neural Netw Learn Syst

مصطلحات موضوعية: Computer Networks and Communications, Computer science, Bioengineering, non-linear regression, 02 engineering and technology, Residual, Convolutional neural network, Article, Robust regression, Bias, Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, full residual deep network, Artificial Intelligence & Image Processing, Imputation (statistics), Artificial neural network, Generalized additive model, encoder-decoder, deep learning, Invariant (physics), Missing data, Autoencoder, Backpropagation, Computer Science Applications, Nonlinear system, prediction of satellite aerosol optical depth (AOD) and PM2.5, spatiotemporal modeling, 020201 artificial intelligence & image processing, Algorithm, Software, Decoding methods

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fcdf659fe2e9837f0167fdf6dcdb4da
https://escholarship.org/uc/item/5bg6p240

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