A novel two-step adaptive multioutput semisupervised soft sensor with applications in wastewater treatment-Reference-Cited by-同舟云学术

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A novel two-step adaptive multioutput semisupervised soft sensor with applications in wastewater treatment

Published:2021-02-07 Issue:23 Volume:28 Page:29131-29145
ISSN:0944-1344
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Li Dong,Huang Daoping,Liu Yiqi^ORCID

Funder

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

Guangdong Technology International Cooperation Project Application

Fundamental Research Funds for the central Universities, SCUT

Hainan Provincial Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s11356-021-12656-9.pdf

Reference38 articles.

1. Al-Janabi S, Alkaim AF (2020) A nifty collaborative analysis to predicting a novel tool (DRFLLS) for missing values estimation. Soft Comput 24:555–569. https://doi.org/10.1007/s00500-019-03972-x

2. Al-Janabi S, Alkaim AF, Adel Z (2020a) An Innovative synthesis of deep learning techniques (DCapsNet & DCOM) for generation electrical renewable energy from wind energy. Soft Comput 24:10943–10962. https://doi.org/10.1007/s00500-020-04905-9

3. Al-Janabi S, Mahdi MA (2019) Evaluation prediction techniques to achievement an optimal biomedical analysis. In J Grid Util Comp 10:512–527. https://doi.org/10.1504/IJGUC.2019.10020511

4. Al-Janabi S, Mohammad M, Al-Sultan A (2020b) A new method for prediction of air pollution based on intelligent computation. Soft Comput 24:661–680. https://doi.org/10.1007/s00500-019-04495-1

5. Al Janabi S (2018) Smart system to create an optimal higher education environment using IDA and IOTs. Int J Comput Appl 42:244–259. https://doi.org/10.1080/1206212x.2018.1512460

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1. Design and application of soft sensors in rural sewage treatment facilities;AQUA — Water Infrastructure, Ecosystems and Society;2023-11-01

2. Modeling an Adaptive Hybrid Soft Sensor with Co-training Learning toward Applications in Wastewater Treatment;Industrial & Engineering Chemistry Research;2023-10-09

3. Energy Consumption Prediction Model of Wastewater Treatment Plant Based on Stochastic Configuration Networks;2023 International Conference on Power Energy Systems and Applications (ICoPESA);2023-02-24

4. Development of an Adversarial Transfer Learning-Based Soft Sensor in Industrial Systems;IEEE Transactions on Instrumentation and Measurement;2023

5. Recent Advancement and Efficiency Hindering Factors in the Wastewater Treatment Plant: A Review;Recent Trends in Wastewater Treatment;2022

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