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A comparative survey between cascade correlation neural network (CCNN) and feedforward neural network (FFNN) machine learning models for forecasting …
B Joshi, VK Singh, DK Vishwakarma, MA Ghorbani… - Scientific Reports, 2024 - nature.com
Suspended sediment concentration prediction is critical for the design of reservoirs, dams,
rivers ecosystems, various operations of aquatic resource structure, environmental safety …
rivers ecosystems, various operations of aquatic resource structure, environmental safety …
Stacked hybridization to enhance the performance of artificial neural networks (ANN) for prediction of water quality index in the Bagh river basin, India
Water quality assessment is paramount for environmental monitoring and resource
management, particularly in regions experiencing rapid urbanization and industrialization …
management, particularly in regions experiencing rapid urbanization and industrialization …
Multi-ahead electrical conductivity forecasting of surface water based on machine learning algorithms
The present research work focused on predicting the electrical conductivity (EC) of surface
water in the Upper Ganga basin using four machine learning algorithms: multilayer …
water in the Upper Ganga basin using four machine learning algorithms: multilayer …
[HTML][HTML] A data-driven approach to river discharge forecasting in the Himalayan region: Insights from Aglar and Paligaad rivers
This study aims to better understand the time series forecasting of Aglar and Paligaad rivers'
discharge (which has a significant impact on the Himalayan river) using advanced time …
discharge (which has a significant impact on the Himalayan river) using advanced time …
Modeling of soil moisture movement and wetting behavior under point-source trickle irrigation
The design and selection of ideal emitter discharge rates can be aided by accurate
information regarding the wetted soil pattern under surface drip irrigation. The current field …
information regarding the wetted soil pattern under surface drip irrigation. The current field …
Daily suspended sediment yield estimation using soft-computing algorithms for hilly watersheds in a data-scarce situation: a case study of Bino watershed …
Water erosion creates adverse impacts on agricultural production, infrastructure, and water
quality across the world, especially in hilly areas. Regional-scale water erosion assessment …
quality across the world, especially in hilly areas. Regional-scale water erosion assessment …
Hybrid river stage forecasting based on machine learning with empirical mode decomposition
The river stage is certainly an important indicator of how the water level fluctuates overtime.
Continuous control of the water stage can help build an early warning indicator of floods …
Continuous control of the water stage can help build an early warning indicator of floods …
Estimation of crop evapotranspiration using statistical and machine learning techniques with limited meteorological data: a case study in Udham Singh Nagar, India
Accurate forecasting of daily evapotranspiration (ET) is essential for enhancing real-time
irrigation scheduling and informed decision-making in water resources allocation. This study …
irrigation scheduling and informed decision-making in water resources allocation. This study …
Evaluation of CatBoost method for predicting weekly Pan evaporation in subtropical and sub-humid regions
Pan evaporation modeling and forecasting are needed to provide timely, continuous, and
valuable information to support water management. This study aimed to overcome the …
valuable information to support water management. This study aimed to overcome the …
Sensitivity of daily reference evapotranspiration to weather variables in tropical savanna: a modelling framework based on neural network
Accurate prediction of reference evapotranspiration (ETo) is crucial for many water-related
fields, including crop modelling, hydrologic simulations, irrigation scheduling and …
fields, including crop modelling, hydrologic simulations, irrigation scheduling and …