Research graph
References from Prediction of Crop Water Requirements in the Chushandian Irrigation District Based on TA-Bi-GRU. Local targets link to admitted publications; unresolved targets remain external evidence.
Review of Conceptual and Systematic Progress of Precision Irrigation
2021 · External reference
IWRAM: A Hybrid Model for Irrigation Water Demand Forecasting to Quantify the Impacts of Climate Change
10.1016/j.agwat.2023.108643 · 2024 · External reference
Prediction of Irrigation Water Requirements for Green Beans Based on Machine-Learning Algorithms in Arid Region
10.1007/s11269-023-03443-x · 2023 · External reference
Prediction Accuracy for Projectwide Evapotranspiration Using Crop Coefficients and Reference Evapotranspiration
10.1061/(asce)0733-9437(2005)131:1(24) · 2005 · External reference
Unresolved reference
External reference
Calibration of Two Models for Estimating Reference Evapotranspiration by Using FAO-56 Penman-Monteith Model under Arid Conditions
10.26480/gwk.02.2023.113.121 · 2023 · External reference
Analysis of Crop Water Requirements and Irrigation Demands for Rice: Implications for Increasing Effective Rainfall
10.1016/j.agwat.2021.107285 · 2022 · External reference
10.3390/w14162578
10.3390/w14162578 · External reference
Evaluation of Random Forests and Generalized Regression Neural Networks for Daily Reference Evapotranspiration Modelling
10.1016/j.agwat.2017.08.003 · 2017 · External reference
Light Gradient Boosting Machine: An Efficient Soft Computing Model for Estimating Daily Reference Evapotranspiration with Local and External Meteorological Data
10.1016/j.agwat.2019.105758 · 2019 · External reference
Estimation of Daily Maize Transpiration Using Support Vector Machines, Extreme Gradient Boosting, Artificial and Deep Neural Networks Models
10.1016/j.agwat.2020.106547 · 2021 · External reference
Nation-Scale Reference Evapotranspiration Estimation by Using Deep Learning and Classical Machine Learning Models in China
10.1016/j.jhydrol.2021.127207 · 2022 · External reference
Short-Term Daily Reference Evapotranspiration Forecasting Using Temperature-Based Deep Learning Models in Different Climate Zones in China
10.1016/j.agwat.2023.108498 · 2023 · External reference
Comparative Analysis of Advanced Deep Learning Models for Predicting Evapotranspiration Based on Meteorological Data in Bangladesh
10.1007/s11356-024-35182-w · 2024 · External reference
Reference Crop Evapotranspiration Prediction Based on Gated Recurrent Unit with Quantum-Inspired Multi-Head Self-Attention Mechanism
10.1007/s11269-024-04016-2 · 2025 · External reference
Demand Prediction of Rice Growth Stage-Wise Irrigation Water Requirement and Fertilizer Using Bayesian Genetic Algorithm and Random Forest for Yield Enhancement
10.1007/s10333-023-00930-0 · 2023 · External reference
10.1109/icdsns62112.2024.10691309
10.1109/icdsns62112.2024.10691309 · External reference
Attention Is All Water Need: Multistep Time Series Irrigation Water Demand Forecasting in Irrigation Districts
2024 · External reference
Bidirectional Recurrent Neural Networks
10.1109/78.650093 · 1997 · External reference
10.3390/su132313384
10.3390/su132313384 · External reference
10.3390/en12061140
10.3390/en12061140 · External reference
Unresolved reference
External reference
10.3115/v1/d14-1179
10.3115/v1/d14-1179 · External reference
Construction Machine Pose Prediction Considering Historical Motions and Activity Attributes Using Gated Recurrent Unit (GRU)
10.1016/j.autcon.2020.103444 · 2021 · External reference
Enhancing Sustainability of Electric Vehicles: A Field Study Approach to Understanding User Acceptance and Behavior
2012 · External reference
Forecasting Daily Potential Evapotranspiration Using Machine Learning and Limited Climatic Data
2011 · External reference
Shale Content Prediction of Well Logs Based on CNN-BiGRU-VAE Neural Network
10.1007/s12040-023-02164-4 · 2023 · External reference
Demand Prediction of Rice Growth Stage-Wise Irrigation Water Requirement and Fertilizer Using Bayesian Genetic Algorithm and Random Forest for Yield Enhancement
10.1007/s10333-023-00930-0 · ExternalCitation · doi-reference
Prediction of Irrigation Water Requirements for Green Beans Based on Machine-Learning Algorithms in Arid Region
10.1007/s11269-023-03443-x · ExternalCitation · doi-reference
Reference Crop Evapotranspiration Prediction Based on Gated Recurrent Unit with Quantum-Inspired Multi-Head Self-Attention Mechanism
10.1007/s11269-024-04016-2 · ExternalCitation · doi-reference
Comparative Analysis of Advanced Deep Learning Models for Predicting Evapotranspiration Based on Meteorological Data in Bangladesh
10.1007/s11356-024-35182-w · ExternalCitation · doi-reference
Shale Content Prediction of Well Logs Based on CNN-BiGRU-VAE Neural Network
10.1007/s12040-023-02164-4 · ExternalCitation · doi-reference
Evaluation of Random Forests and Generalized Regression Neural Networks for Daily Reference Evapotranspiration Modelling
10.1016/j.agwat.2017.08.003 · ExternalCitation · doi-reference
Light Gradient Boosting Machine: An Efficient Soft Computing Model for Estimating Daily Reference Evapotranspiration with Local and External Meteorological Data
10.1016/j.agwat.2019.105758 · ExternalCitation · doi-reference
Estimation of Daily Maize Transpiration Using Support Vector Machines, Extreme Gradient Boosting, Artificial and Deep Neural Networks Models
10.1016/j.agwat.2020.106547 · ExternalCitation · doi-reference
Analysis of Crop Water Requirements and Irrigation Demands for Rice: Implications for Increasing Effective Rainfall
10.1016/j.agwat.2021.107285 · ExternalCitation · doi-reference
Short-Term Daily Reference Evapotranspiration Forecasting Using Temperature-Based Deep Learning Models in Different Climate Zones in China
10.1016/j.agwat.2023.108498 · ExternalCitation · doi-reference
IWRAM: A Hybrid Model for Irrigation Water Demand Forecasting to Quantify the Impacts of Climate Change
10.1016/j.agwat.2023.108643 · ExternalCitation · doi-reference
Construction Machine Pose Prediction Considering Historical Motions and Activity Attributes Using Gated Recurrent Unit (GRU)
10.1016/j.autcon.2020.103444 · ExternalCitation · doi-reference
Nation-Scale Reference Evapotranspiration Estimation by Using Deep Learning and Classical Machine Learning Models in China
10.1016/j.jhydrol.2021.127207 · ExternalCitation · doi-reference
Prediction Accuracy for Projectwide Evapotranspiration Using Crop Coefficients and Reference Evapotranspiration
10.1061/(asce)0733-9437(2005)131:1(24) · ExternalCitation · doi-reference
Bidirectional Recurrent Neural Networks
10.1109/78.650093 · ExternalCitation · doi-reference
10.1109/icdsns62112.2024.10691309
10.1109/icdsns62112.2024.10691309 · ExternalCitation · doi-reference
Calibration of Two Models for Estimating Reference Evapotranspiration by Using FAO-56 Penman-Monteith Model under Arid Conditions
10.26480/gwk.02.2023.113.121 · ExternalCitation · doi-reference
10.3115/v1/d14-1179
10.3115/v1/d14-1179 · ExternalCitation · doi-reference
10.3390/en12061140
10.3390/en12061140 · ExternalCitation · doi-reference
10.3390/su132313384
10.3390/su132313384 · ExternalCitation · doi-reference
10.3390/w14162578
10.3390/w14162578 · ExternalCitation · doi-reference
