AIMC Topic: Seasons

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High spatiotemporal resolution estimation and analysis of global surface CO concentrations using a deep learning model.

Journal of environmental management Nov 1, 2024
Ambient carbon monoxide (CO) is a primary air pollutant that poses significant health risks and contributes to the formation of secondary atmospheric pollutants, such as ozone (O). This study aims to elucidate global CO pollution in relation to healt...
Environmental Monitoring Air Pollutants Seasons Carbon Monoxide Ozone Neural Networks, Computer Deep Learning China
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Hypoxia extreme events in a changing climate: Machine learning methods and deterministic simulations for future scenarios development in the Venice Lagoon.

Marine pollution bulletin Oct 3, 2024
Climate change pressures include the dissolved oxygen decline that in lagoon ecosystems can lead to hypoxia, i.e. low dissolved oxygen concentrations, which have consequences to ecosystem functioning including biogeochemical cycling from mild to seve...
Models, Theoretical Environmental Monitoring Oxygen Water Quality Climate Change Italy Seawater Seasons Machine Learning Ecosystem
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Development, study, and comparison of models of cross-immunity to the influenza virus using statistical methods and machine learning.

Voprosy virusologii Sep 26, 2024
INTRODUCTION: The World Health Organization considers the values of antibody titers in the hemagglutination inhibition assay as one of the most important criteria for assessing successful vaccination. Mathematical modeling of cross-immunity allows fo...
Influenza, Human Seasons Cross Reactions Hemagglutination Inhibition Tests Influenza Vaccines Antibodies, Viral Vaccination Humans Machine Learning
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Parametric seasonal-trend autoregressive neural network for long-term crop price forecasting.

PloS one Sep 26, 2024
Crop price forecasting is difficult in that supply is not as elastic as demand, therefore, supply and demand should be stabilized through long-term forecasting and pre-response to the price. In this study, we propose a Parametric Seasonal-Trend Autor...
Commerce Raphanus Seasons Crops, Agricultural Neural Networks, Computer Forecasting
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Unravelling nitrate transformation mechanisms in karst catchments through the coupling of high-frequency sensor data and machine learning.

Water research Sep 23, 2024
Nitrate dynamics within a catchment are critical to the earth's system process, yet the intricate details of its transport and transformation at high resolutions remain elusive. Hydrological effects on nitrate dynamics in particular have not been tho...
Water Pollutants, Chemical Seasons Nitrates Machine Learning Environmental Monitoring
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Rice yield prediction through integration of biophysical parameters with SAR and optical remote sensing data using machine learning models.

Scientific reports Sep 17, 2024
In an era marked by growing global population and climate variability, ensuring food security has become a paramount concern. Rice, being a staple crop for billions of people, requires accurate and timely yield prediction to ensure global food securi...
Remote Sensing Technology Oryza Seasons Neural Networks, Computer Machine Learning Crops, Agricultural Radar
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Forecasting for Haditha reservoir inflow in the West of Iraq using Support Vector Machine (SVM).

PloS one Sep 6, 2024
Accurate inflow forecasting is an essential non-engineering strategy to guarantee flood management and boost the effectiveness of the water supply. As inflow is the primary reservoir input, precise inflow forecasting may also offer appropriate reserv...
Water Supply Support Vector Machine Iraq Forecasting Seasons Rivers
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Estimating epidemic trajectories of SARS-CoV-2 and influenza A virus based on wastewater monitoring and a novel machine learning algorithm.

The Science of the total environment Aug 27, 2024
The COVID-19 pandemic has altered the circulation of non-SARS-CoV-2 respiratory viruses. In this study, we carried out wastewater surveillance of SARS-CoV-2 and influenza A virus (IAV) in three key port cities in China through real-time quantitative ...
Wastewater-Based Epidemiological Monitoring Influenza, Human Seasons Influenza A virus Algorithms Humans China SARS-CoV-2 Machine Learning Real-Time Polymerase Chain Reaction
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Predicting rice phenology across China by integrating crop phenology model and machine learning.

The Science of the total environment Aug 21, 2024
This study explores the integration of crop phenology models and machine learning approaches for predicting rice phenology across China, to gain a deeper understanding of rice phenology prediction. Multiple approaches were used to predict heading and...
China Agriculture Seasons Crops, Agricultural Oryza Machine Learning Climate
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Artificial neural networks as a tool for seasonal forecast of attack intensity of Spodoptera spp. in Bt soybean.

International journal of biometeorology Aug 13, 2024
Soybean (Glycine max) is the world's most cultivated legume; currently, most of its varieties are Bt. Spodoptera spp. (Lepidoptera: Noctuidae) are important pests of soybean. An artificial neural network (ANN) is an artificial intelligence tool that ...
Weather Seasons Plants, Genetically Modified Spodoptera Forecasting Glycine max Neural Networks, Computer Animals Larva
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