H-ConvLSTM to Estimate Reference Evapotranspiration From Air Temperature and Relative Humidity
The estimation of evapotranspiration reference is significant importance in the agricultural sector, as it allows for the precise determination of irrigation water distribution times. A few deep learning architecture models are employed by researchers in the estimation of evapotranspiration referenc...
Saved in:
Main Authors: | Abdul Haris, M. Marimin, Sri Wahjuni, Budi Indra Setiawan |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/11068947/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Driving Behavior Classification Using a ConvLSTM
by: Alberto Pingo, et al.
Published: (2025-05-01) -
Combustion Field Prediction and Diagnosis via Spatiotemporal Discrete U-ConvLSTM Model
by: Xiaodong Huang, et al.
Published: (2024-01-01) -
Real-Time Human Action Recognition With Dynamical Frame Processing via Modified ConvLSTM and BERT
by: Raden Hadapiningsyah Kusumoseniarto, et al.
Published: (2025-01-01) -
ED-SA-ConvLSTM: A Novel Spatiotemporal Prediction Model and Its Application in Ionospheric TEC Prediction
by: Yalan Li, et al.
Published: (2025-06-01) -
Impacts of climatology error on evapotranspiration data merging over the intensively irrigated Haihe river basin, China
by: Yuxi Li, et al.
Published: (2025-08-01)