AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Droughts

Showing 11 to 20 of 36 articles

Clear Filters

Comparison of hybrid machine learning models to predict short-term meteorological drought in Guanzhong region, China.

Water science and technology : a journal of the International Association on Water Pollution Research
Reliable drought prediction plays a significant role in drought management. Applying machine learning models in drought prediction is getting popular in recent years, but applying the stand-alone models to capture the feature information is not suffi...

Application of empirical mode decomposition, particle swarm optimization, and support vector machine methods to predict stream flows.

Environmental monitoring and assessment
Modeling stream flows is vital for water resource planning and flood and drought management. In this study, the performance of hybrid models constructed by combining least square support vector machines (LSSVM), empirical model decomposition (EMD), a...

Multimodal deep learning-based drought monitoring research for winter wheat during critical growth stages.

PloS one
Wheat is a major grain crop in China, accounting for one-fifth of the national grain production. Drought stress severely affects the normal growth and development of wheat, leading to total crop failure, reduced yields, and quality. To address the la...

An enhanced drought forecasting in coastal arid regions using deep learning approach with evaporation index.

Environmental research
Coastal arid regions are similar to deserts, where it receives significantly less rainfall, less than 10 cm. Perhaps the world's worst natural disaster, coastal area droughts, can only be detected using reliable monitoring systems. Creating a reliabl...

Fusion-based approach for hydrometeorological drought modeling: a regional investigation for Iran.

Environmental science and pollution research international
The objective of this study was to model a new drought index called the Fusion-based Hydrological Meteorological Drought Index (FHMDI) to simultaneously monitor hydrological and meteorological drought. Aiming to estimate drought more accurately, loca...

An evaluative technique for drought impact on variation in agricultural LULC using remote sensing and machine learning.

Environmental monitoring and assessment
Drought events threaten freshwater reservoirs and agricultural productivity, particularly in semi-arid regions characterized by erratic rainfall. This study evaluates a novel technique for assessing the impact of drought on LULC variations in the con...

Enhancing drought resilience: machine learning-based vulnerability assessment in Uttar Pradesh, India.

Environmental science and pollution research international
Drought is a natural and complex climatic hazard. It has both natural and social connotations. The purpose of this study is to use machine learning methods (MLAs) for drought vulnerability (DVM) in Uttar Pradesh, India. There were 18 factors used to ...

Utilizing machine learning and bioinformatics analysis to identify drought-responsive genes affecting yield in foxtail millet.

International journal of biological macromolecules
Drought stress is a major constraint on crop development, potentially causing huge yield losses and threatening global food security. Improving Crop's stress tolerance is usually associated with a yield penalty. One way to balance yield and stress to...

Integrating non-invasive VIS-NIR and bioimpedance spectroscopies for stress classification of sweet basil (Ocimum basilicum L.) with machine learning.

Biosensors & bioelectronics
Plant stress diagnosis is essential for efficient crop management and productivity increase. Under stress, plants undergo physiological and compositional changes. Vegetation indices obtained from leaf reflectance spectra and bioimpedance spectroscopy...

Examining optimized machine learning models for accurate multi-month drought forecasting: A representative case study in the USA.

Environmental science and pollution research international
The Colorado River has experienced a significant streamflow reduction in recent decades due to climate change, resulting in pronounced hydrological droughts that pose challenges to the environment and human activities. However, current models struggl...