A Hybrid LSTM Approach for Irrigation Scheduling in Maize Crop

A Hybrid LSTM Approach for Irrigation Scheduling in Maize Crop

Irrigation plays a crucial role in maize cultivation, as watering is essential for optimizing crop yield and quality, particularly given maize’s sensitivity to soil moisture variations. In the current study, a hybrid Long Short-Term Memory (LSTM) approach is presented aiming to predict irrigation sc...

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Bibliographic Details
Main Authors: Konstantinos Dolaptsis, Xanthoula Eirini Pantazi, Charalampos Paraskevas, Selçuk Arslan, Yücel Tekin, Bere Benjamin Bantchina, Yahya Ulusoy, Kemal Sulhi Gündoğdu, Muhammad Qaswar, Danyal Bustan, Abdul Mounem Mouazen
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Agriculture
Subjects:
precision agriculture
artificial intelligence
long short-term memory
predictive control
deep learning
moisture content
Online Access:https://www.mdpi.com/2077-0472/14/2/210

Internet

https://www.mdpi.com/2077-0472/14/2/210

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