AIMC Topic: Water

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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...
Neural Networks, Computer Algorithms Crops, Agricultural Agricultural Irrigation Water Agriculture Climate Change Forecasting Deep Learning
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A robust deep learning model for predicting green tea moisture content during fixation using near-infrared spectroscopy: Integration of multi-scale feature fusion and attention mechanisms.

Food research international (Ottawa, Ont.) Jan 30, 2025
Fixation is a critical step in green tea processing, and the moisture content of the leaves after fixation is a key indicator of the fixation quality. Near-infrared spectroscopy (NIRS)-based moisture detection technology is often applied in the tea p...
Spectroscopy, Near-Infrared Deep Learning Water Temperature Food Handling Plant Leaves Tea Least-Squares Analysis
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Deep learning-based free-water correction for single-shell diffusion MRI.

Magnetic resonance imaging Jan 17, 2025
Free-water elimination (FWE) modeling in diffusion magnetic resonance imaging (dMRI) is crucial for accurate estimation of diffusion properties by mitigating the partial volume effects caused by free water, particularly at the interface between white...
Humans Algorithms Adult Brain Female Brain Neoplasms White Matter Male Aged Connectome Young Adult Diffusion Magnetic Resonance Imaging Deep Learning Water Image Processing, Computer-Assisted
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WALINET: A water and lipid identification convolutional neural network for nuisance signal removal in MR spectroscopic imaging.

Magnetic resonance in medicine Dec 31, 2024
PURPOSE: Proton magnetic resonance spectroscopic imaging ( -MRSI) provides noninvasive spectral-spatial mapping of metabolism. However, long-standing problems in whole-brain -MRSI are spectral overlap of metabolite peaks with large lipid signal fro...
Humans Neural Networks, Computer Algorithms Brain Water Image Processing, Computer-Assisted Magnetic Resonance Imaging Male Deep Learning Female Convolutional Neural Networks Lipids Adult Magnetic Resonance Spectroscopy Proton Magnetic Resonance Spectroscopy
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Determination and visualization of moisture content in Camellia oleifera seeds rapidly based on hyperspectral imaging combined with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 27, 2024
Moisture content (MC) is crucial for the storage, transportation, and processing of Camellia oleifera seeds. The purpose of this study was to investigate the feasibility for detecting MC in Camellia oleifera seeds using visible near-infrared hyperspe...
Hyperspectral Imaging Camellia Support Vector Machine Seeds Least-Squares Analysis Deep Learning Water Neural Networks, Computer Algorithms Spectroscopy, Near-Infrared
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Network embedding: The bridge between water distribution network hydraulics and machine learning.

Water research Dec 19, 2024
Machine learning has been increasingly used to solve management problems of water distribution networks (WDNs). A critical research gap, however, remains in the effective incorporation of WDN hydraulic characteristics in machine learning. Here we pre...
Water Water Supply Machine Learning Algorithms
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A rapid method for assessing seed drought resistance using integrated ID-BOA-SVM.

Analytical methods : advancing methods and applications Dec 5, 2024
This study investigates the application of near-infrared spectroscopy (NIR) for assessing drought resistance in seeds, aiming to offer a rapid and efficient method suitable for large-scale primary screening. NIR spectroscopy is utilized to analyze fo...
Drought Resistance Water Support Vector Machine Seeds Bayes Theorem Spectroscopy, Near-Infrared Zea mays Droughts
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Classification of glucose-level in deionized water using machine learning models and data pre-processing technique.

PloS one Dec 5, 2024
Accurate monitoring of glucose levels is essential in the field of diabetes detection and prevention to ensure appropriate treatment planning. Conventional blood glucose monitoring methods, although widely used, are intrusive and frequently result in...
Support Vector Machine Glucose Humans Blood Glucose Machine Learning Water Spectrum Analysis, Raman
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Stacked Ensemble with Machine Learning Regressors on Optimal Features (SMOF) of hyperspectral sensor PRISMA for inland water turbidity prediction.

Environmental science and pollution research international Nov 25, 2024
Leveraging hyperspectral data across various domains yields substantial benefits, yet managing many spectral bands and identifying the essential ones poses a formidable challenge. This study identifies the most relevant bands within a hyperspectral d...
Spectrum Analysis Machine Learning Water Environmental Monitoring
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Machine learning models for prediction of nutrient concentrations in surface water in an agricultural watershed.

Journal of environmental management Nov 19, 2024
Prediction and quantification of nutrient concentrations in surface water has gained substantial attention during recent decades because excess nutrients released from agricultural and urban watersheds can significantly deteriorate surface water qual...
Water Nutrients Agriculture Phosphorus Machine Learning Models, Theoretical Water Quality
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