Aqua Status Prediction Using IoT and Optimization in Aquaculture: A Comprehensive Review-Reference-Cited by-同舟云学术

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Aqua Status Prediction Using IoT and Optimization in Aquaculture: A Comprehensive Review

Published:2024-04-25 Issue: Volume:6 Page:1-4
ISSN:
Container-title:2024 MIT Art, Design and Technology School of Computing International Conference (MITADTSoCiCon)
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Author:

Londhe Aoudumber¹,Apare Ravindra²,Borhade Ravindra¹

Affiliation:

1. Savitribai Phule Pune University,Smt. Kashibai Navale College of Engineering,Department of Computer Engineering,Pune,India

2. Savitribai Phule Pune University,Trinity College of Engineering & Research,Department of Information Technology,Pune,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10574857/10574907/10575248.pdf?arnumber=10575248

Reference26 articles.

1. Smart Water Quality Prediction Using Atom Search Optimization with Fuzzy Deep Convolutional Network

2. IWQP4Net: An Efficient Convolution Neural Network for Irrigation Water Quality Prediction

3. Chronological Harris hawks‐based deep LSTM classifier in wireless sensor network for aqua status prediction

4. Short-term water level prediction using neural networks and neuro-fuzzy approach

5. RideNN: A New Rider Optimization Algorithm-Based Neural Network for Fault Diagnosis in Analog Circuits

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