Fish weight prediction using empirical and data-driven models in aquaculture systems-Reference-Cited by-同舟云学术

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Fish weight prediction using empirical and data-driven models in aquaculture systems

Published:2024-08-21 Issue: Volume:17 Page:369-374
ISSN:
Container-title:2024 IEEE Conference on Control Technology and Applications (CCTA)
language:
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Author:

Chen Xiao¹,N’Doye Ibrahima²,Aljehani Fahad¹,Laleg-Kirati Taous-Meriem³

Affiliation:

1. King Abdullah University of Science and Technology (KAUST),Computer, Electrical and Mathematical Science and Engineering Division (CEMSE),Saudi Arabia,23955-6900

2. King Abdullah University of Science and Technology (KAUST),Environmental Science and Engineering Program, Biological and Environmental Science and Engineering Division,Saudi Arabia,23955-6900

3. Paris-Saclay,National Institute for Research in Digital Science and Technology (INRIA),France

Funder

King Abdullah University of Science and Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10666388/10666504/10666549.pdf?arnumber=10666549

Reference23 articles.

1. The state of world fisheries and aquaculture

2. Growth models of gilthead sea bream ( Sparus aurata L.) for aquaculture: A review

3. Trends in Growth Modeling in Fisheries Science

4. Models for estimating feed intake in aquaculture: A review

5. How growth relates to ration size;Talbot;Fish Farmer,1994

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