An artificial neural network-particle swarm optimization (ANN-PSO) approach to predict the aeration efficiency of venturi aeration system-Reference-Cited by-同舟云学术

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An artificial neural network-particle swarm optimization (ANN-PSO) approach to predict the aeration efficiency of venturi aeration system

Published:2023-08 Issue: Volume:4 Page:100230
ISSN:2772-3755
Container-title:Smart Agricultural Technology
language:en
Short-container-title:Smart Agricultural Technology

Author:

Yadav Anamika^ORCID,Roy Subha M.

Publisher

Elsevier BV

Subject

Artificial Intelligence,General Agricultural and Biological Sciences,Computer Science (miscellaneous)

Reference55 articles.

1. Performance of closed loop venturi aspirated aeration system: experimental study and numerical analysis with discrete bubble model;Mahmud;Water,2020

2. Applications of venturi principle to water aeration systems;Baylar;Environ. Fluid Mech.,2006

3. Dissolved-oxygen concentrations in pond aquaculture;Boyd;Global Aquacult. All.,2010

4. Aeration characteristics of a rectangular stepped cascade system;Moulick;Water Sci Technol,2010

5. Applications of gravity aeration system in aquaculture—a systematic review;Roy;Aquacult. Int.,2022

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1. Dynamic liquid level prediction in oil wells during oil extraction based on WOA-AM-LSTM-ANN model using dynamic and static information;Energy;2023-11

2. Artificial intelligence-based approach for improving the aeration efficiency of a perforated plate aeration system;Multiscale and Multidisciplinary Modeling, Experiments and Design;2023-10-10

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