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Prediction of dissolved oxygen content changes based on two-dimensional behavior features of fish school and T–S fuzzy neural network

  • Published:2022-09 Issue:3 Volume:15 Page:210-217
  • ISSN:1674-2370
  • Container-title:Water Science and Engineering
  • language:en
  • Short-container-title:Water Science and Engineering

Author:

Bao Yu-jun,Ji Chang-ying,Zhang Bing

Funder

Natural Science Foundation of Changzhou City

Ministry of Education of the People's Republic of China

Publisher

Elsevier BV

Subject

Ocean Engineering,Civil and Structural Engineering

Reference23 articles.

1. Representation of freshwater aquaculture fish behavior in low dissolved oxygen condition based on 3D computer vision;Bao;Mod. Phys. Lett. B,2018

2. Prediction model of dissolved oxygen in aquaculture based on improved long short-term memory neural network;Cao;Trans. Chin. Soc. Agric. Eng.,2021

3. Vision-based real-time monitoring on the behavior of fish school;Chew,2009

4. A video multitracking system for quantification of individual behavior in a large fish shoal: Advantages and limits;Delcourt;Behav. Res. Methods,2009

5. Modeling hourly dissolved oxygen concentration (DO) using two different adaptive neuro–fuzzy inference systems (ANFIS): A comparative study;Heddam;Environ. Monit. Assess.,2014

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