A Comparative Study of LSTM, GRU, BiLSTM and BiGRU to Predic…

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18
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21
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2023
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  • DOI 10.1109/jcsse58229.2023.10202128
  • OpenAlex ID W4385730485
  • Type Conference-paper
  • Language EN
  • Published 28 Jun 2023
  • Pages 67–72
  • Source International Joint Conference on Comput…
  • FWCI 16.41
  • Countries 1
  • Institutions 1
  • Added 11 Aug 2023
  • Updated 16 Oct 2026
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A Comparative Study of LSTM, GRU, BiLSTM and BiGRU to Predict Dissolved Oxygen

Conference-paper 2023 EN

In aquaculture, dissolved oxygen (DO) levels affect fish growth and survival. Automated monitoring and prediction of DO is challenging and becomes expensive if unnecessary sensors are used. This study aims to identify the optimal water and environmental parameters for DO prediction. Data from the fishpond station of Rajabhat Rajanagarindra University were pre-processed and used for training using…

18

Citations

21

References

3

Authors

16.41

FWCI

Citations by Year
Last 3 years
Topics
Keywords
UN Sustainable Development Goals
1 SDGs
Authors & Affiliations
3 authors
#AuthorInstitutionsORCID
1 Narongsak Putpuek Rajabhat Rajanagarindra Univer… (TH) —
2 Apiradee Putpuek Rajabhat Rajanagarindra Univer… (TH) —
3 A. Sungthong Rajabhat Rajanagarindra Univer… (TH) —

Data: OpenAlex