AIMC Topic: Agricultural Irrigation
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Smart IoT-driven precision agriculture: Land mapping, crop prediction, and irrigation system.
PloS one
Mar 18, 2025
As the world population is increasing day by day, so is the need for more advanced automated precision agriculture to meet the increasing demands for food while decreasing labor work and saving water for crops. Recently, there have been many studies ...
Physics-informed neural networks for enhanced reference evapotranspiration estimation in Morocco: Balancing semi-physical models and deep learning.
Chemosphere
Feb 20, 2025
Reference evapotranspiration (ETo) is essential for agricultural water management, crop productivity, and irrigation systems. The Penman-Monteith (PM) equation is the standard method for estimating ETo, but its data-intensive nature makes it impracti...
Integrating deep learning algorithms for forecasting evapotranspiration and assessing crop water stress in agricultural water management.
Journal of environmental management
Jan 31, 2025
The increasing impacts of climate change on global agriculture necessitate the development of advanced predictive models for efficient water management in crop fields. This study aims to enhance the forecasting of evapotranspiration (ET), potential e...
The artificial intelligence-based agricultural field irrigation warning system using GA-BP neural network under smart agriculture.
PloS one
Jan 17, 2025
This work explores an intelligent field irrigation warning system based on the Enhanced Genetic Algorithm-Backpropagation Neural Network (EGA-BPNN) model in the context of smart agriculture. To achieve this, irrigation flow prediction in agricultural...
Utilizing convolutional neural network (CNN) for orchard irrigation decision-making.
Environmental monitoring and assessment
Jan 14, 2025
Efficient agricultural management often relies on farmers' experiential knowledge and demands considerable labor, particularly in regions with challenging terrains. To reduce these burdens, the adoption of smart technologies has garnered increasing a...
Deployment of intelligent irrigation monitoring system with Android app for machine learning prediction.
Environmental monitoring and assessment
Nov 21, 2024
Water is a fundamental necessity for humans and a critical resource in agriculture. However, water scarcity poses a significant challenge, especially considering that agriculture accounts for a substantial portion of freshwater usage. The inadequate ...
Fuzzy multi-objective optimization for sustainable agricultural water management of irrigation networks.
Journal of environmental management
Nov 20, 2024
Sustainable water resource management in arid and water deficit regions requires optimal use of water resources due to competition among different water sectors. The purpose of this study is to model uncertainties in economic and hydro-climatic varia...
Machine learning and structural equation modeling for revealing the influence factors and pathways of different water management regimes acting on brown rice cadmium.
The Science of the total environment
Sep 24, 2024
Excessive cadmium (Cd) in brown rice has detrimental effects on rice growth and human health. Water management is a cost-effective, eco-friendly measure to suppress Cd accumulation in rice. However, there is no acknowledged water management regime th...
Evaluation of crop water stress index of wheat by using machine learning models.
Environmental monitoring and assessment
Sep 23, 2024
The Crop Water Stress Index (CWSI), a pivotal indicator derived from canopy temperature, plays a crucial role in irrigation scheduling for water conservation in agriculture. This study focuses on determining CWSI (by empirical method) for wheat crops...
Machine learning-based estimation of evapotranspiration under adaptation conditions: a case study in Heilongjiang Province, China.
International journal of biometeorology
Sep 9, 2024
The prediction of evapotranspiration (ET0) is crucial for agricultural ecosystems, irrigation management, and environmental climate regulation. Traditional methods for predicting ET0 require a variety of meteorological parameters. However, obtaining ...
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