Water Quality Prediction for Smart Aquaculture Using Hybrid Deep Learning Models

Water Quality Prediction for Smart Aquaculture Using Hybrid Deep Learning Models

Water quality prediction (WQP) plays an essential role in water quality management for aquaculture to make aquaculture production profitable and sustainable. In this work, we propose hybrid deep learning (DL) models, convolutional neural network (CNN) with the long short-term memory (LSTM) and gated...

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Bibliographic Details
Main Authors: K. P. Rasheed Abdul Haq, V. P. Harigovindan
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Aquaculture
CNN
deep learning
GRU
hybrid models
LSTM
Online Access:https://ieeexplore.ieee.org/document/9789166/

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