Data-driven management for fuzzy sewage treatment processes using hybrid neural computing-Reference-Cited by-同舟云学术

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Data-driven management for fuzzy sewage treatment processes using hybrid neural computing

Published:2021-01-06 Issue: Volume: Page:
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Zeng Wenru^ORCID,Guo Zhiwei^ORCID,Shen Yu^ORCID,Bashir Ali Kashif^ORCID,Yu Keping^ORCID,Al-Otaibi Yasser D.^ORCID,Gao Xu^ORCID

Funder

National Key Research & Development Program of China

Chongqing basic research and frontier exploration project of China

Chongqing Natural Science Foundation of China

Scientific Program of Chongqing Technology and Business University

Japan Society for the Promotion of Science

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/s00521-020-05655-3.pdf

Reference52 articles.

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2. Pawar P, TarunKumar M, Vittal KP (2020) An IoT based Intelligent smart energy management system with accurate forecasting and load strategy for renewable generation. Measurement 152:107187. https://doi.org/10.1016/j.measurement.2019.107187

3. Zhou X, Li Y, Liang W (2020) CNN-RNN based intelligent recommendation for online medical pre-diagnosis support. IEEE/ACM Trans Comput Biol Bioinforma. https://doi.org/10.1109/tcbb.2020.2994780

4. Zhang X, Yang L, Ding L et al (2020) Sparse vector coding-based multi-carrier NOMA for in-home health networks. IEEE J Sel Areas Commun. https://doi.org/10.1109/JSAC.2020.3020679

5. Zhou YM, Chen YP, Guo JS et al (2019) Recycling of orange waste for single cell protein production and the synergistic and antagonistic effects on production quality. J Clean Prod 213:384–392. https://doi.org/10.1016/j.jclepro.2018.12.168

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