Journal of Zhejiang Agricultural Sciences ›› 2025, Vol. 66 ›› Issue (1): 184-188.DOI: 10.16178/j.issn.0528-9017.20240561

Previous Articles     Next Articles

Research on the prediction of dissolved oxygen content in aquaculture water

XU Hui1(), DENG Haoran2, WANG Zhongpei2, ZHOU Lele2, QIAN Rong2,*()   

  1. 1. School of Information and Artificial Intelligence, Wuhu Institute of Technology, Wuhu 241006, Anhui
    2. Institute of Agricultural Economics and Information, Anhui Academy of Agricultural Sciences, Hefei 230031, Anhui
  • Received:2024-07-10 Online:2025-01-11 Published:2025-01-14

Abstract:

Dissolved oxygen, as a key water quality factor in aquaculture, is closely related to the yield and quality of aquatic products, and accurate prediction of dissolved oxygen content and changes is of great significance for ensuring the safety of aquaculture. In this study, the dissolved oxygen data of the collected aquaculture water were preprocessed, and then combined with the long and short-term memory (LSTM) neural network algorithm, the prediction model of the dissolved oxygen content of the aquaculture water was constructed to predict the dissolved oxygen concentration data at different times in the future, and the prediction accuracy of the prediction model of the dissolved oxygen content of aquaculture water was verified through different prediction accuracy indicators, in order to provide reference for the subsequent research on the prediction of dissolved oxygen content in aquaculture water.

Key words: aquaculture water, dissolved oxygen content, long and short-term memory (LSTM), prediction model

CLC Number: