QGAPHnet : Quantum Genetic Algorithm Based Hybrid QLSTM Model for Soil Moisture Estimation-Reference-Cited by-同舟云学术

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QGAPHnet : Quantum Genetic Algorithm Based Hybrid QLSTM Model for Soil Moisture Estimation

Published:2024-07-07 Issue: Volume:26 Page:5191-5194
ISSN:
Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Sai Sujith¹,Sen Anuvab²,Mallick Chhandak³,Mallik Aakash⁴,Sen Udayon⁵,Paul Mayukhi⁶,Sutradhar Ananya⁵,Roy Subhabrata²

Affiliation:

1. NIT,Department of Chemical Engineering,Rourkela,Odisha,India,769008

2. IIEST Shibpur,Department of ETCE,Howrah,India,711103

3. Jadavpur University,Department of ETCE,Kolkata,India,700032

4. NIT,Department of Electrical and Electronics,Surathkal,Karnataka,India,575025

5. IIEST Shibpur,Department of Computer Science and Technology,Howrah,India,711103

6. IIEST Shibpur,Department of Information Technology,Howrah,India,711103

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10641651.pdf?arnumber=10641651

Reference10 articles.

1. Remote Sensing of Soil Moisture: Recent Advances

2. An Evaluation of Soil Moisture Retrieval Using Machine Learning Methods: Application in Arid Regions of Tunisia

3. Long Short Term Memory (LSTM) based Deep Learning for Sentiment Analysis of English and Spanish Data

4. Soil phosphorus content prediction based on improved PSO-LSTM algorithm

5. Crop Yield Prediction Using CNN-LSTM Model

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