An Ensemble Model for Water Temperature Prediction in Intensive Aquaculture

An Ensemble Model for Water Temperature Prediction in Intensive Aquaculture

In intensive aquaculture systems, accurate water temperature prediction is crucial for aquaculture efficiency. Traditional prediction models often have limitations in dealing with strongly coupled, nonlinear, and time-varying water temperature data. A novel hybrid model for temperature prediction is...

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Bibliographic Details
Main Authors: Mingyan Wang, Qing Xu, Yingying Cao, Shahbaz Gul Hassan, Wenjun Liu, Min He, Tonglai Liu, Longqin Xu, Liang Cao, Shuangyin Liu, Huilin Wu
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Water temperature prediction
combination model
BiLSTM-self attention
variational mode decomposition (VMD)
Online Access:https://ieeexplore.ieee.org/document/10341251/

Internet

https://ieeexplore.ieee.org/document/10341251/

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