AIMC Topic: Climate

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Using artificial neural networks to predict future dryland responses to human and climate disturbances.

Scientific reports Mar 7, 2019
Land degradation and sediment remobilisation in dryland environments is considered to be a significant global environmental problem. Given the potential for currently stabilised dune systems to reactivate under climate change and increased anthropoge...
Ecosystem Climate Change Climate Grassland Humans Neural Networks, Computer
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Urban population exposure to tropospheric ozone: A multi-country forecasting of SOMO35 using artificial neural networks.

Environmental pollution (Barking, Essex : 1987) Oct 13, 2018
Urban population exposure to tropospheric ozone is a serious health concern in Europe countries. Although there are insufficient evidence to derive a level below which ozone has no effect on mortality WHO (World Health Organization) uses SOMO35 (sum ...
Europe Air Pollutants Ozone Environmental Exposure Humans Neural Networks, Computer Forecasting Urban Population Linear Models Climate
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A bioavailable strontium isoscape for Western Europe: A machine learning approach.

PloS one May 30, 2018
Strontium isotope ratios (87Sr/86Sr) are gaining considerable interest as a geolocation tool and are now widely applied in archaeology, ecology, and forensic research. However, their application for provenance requires the development of baseline mod...
Geography Atmosphere Geology Strontium Isotopes Regression Analysis Machine Learning Linear Models Algorithms Climate Environmental Monitoring Europe
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Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset.

International journal of biometeorology Apr 11, 2018
Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial...
Machine Learning Poland Plants Climate Plant Physiological Phenomena Plant Development Meteorology
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The utility of LASSO-based models for real time forecasts of endemic infectious diseases: A cross country comparison.

Journal of biomedical informatics Feb 27, 2018
INTRODUCTION: Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control methods at an early stage of disease outbreaks. Climatic variables has been identified as important pre...
Taiwan Singapore Malaria Japan Thailand Incidence Models, Statistical Infectious Disease Medicine Hand, Foot and Mouth Disease Chickenpox Climate Wavelet Analysis Communicable Disease Control Dengue Humans Machine Learning Algorithms Forecasting Communicable Diseases Reproducibility of Results Public Health Disease Outbreaks
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Eyes on our planet.

Current biology : CB Feb 6, 2018
Combining several satellite-based tracking technologies with big data methods and machine learning, fisheries experts can now efficiently monitor the entirety of the oceans and ensure that legal limits and protected areas are respected. Observing our...
Machine Learning Meteorology Climate Conservation of Natural Resources Big Data Oceans and Seas Remote Sensing Technology Fisheries Spacecraft
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Developing a dengue forecast model using machine learning: A case study in China.

PLoS neglected tropical diseases Oct 16, 2017
BACKGROUND: In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine lea...
Humans Machine Learning Predictive Value of Tests Linear Models Climate Dengue Public Health Algorithms Disease Outbreaks Forecasting China Temperature Incidence
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High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models.

PloS one Jan 23, 2017
Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effecti...
Remote Sensing Technology Burkina Faso Forests Crops, Agricultural Linear Models Climate Machine Learning Soil Support Vector Machine
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The effect of geographical indices on left ventricular structure in healthy Han Chinese population.

International journal of biometeorology Jul 28, 2016
The left ventricular posterior wall thickness (LVPWT) and interventricular septum thickness (IVST) are generally regarded as the functional parts of the left ventricular (LV) structure. This paper aims to examine the effects of geographical indices o...
Climate Weather Reference Values Healthy Volunteers Neural Networks, Computer China Humans Young Adult Female Adolescent Aged Adult Heart Ventricles Aged, 80 and over Asian People Male Middle Aged
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Morbidity Rate Prediction of Dengue Hemorrhagic Fever (DHF) Using the Support Vector Machine and the Aedes aegypti Infection Rate in Similar Climates and Geographical Areas.

PloS one May 11, 2015
BACKGROUND: In the past few decades, several researchers have proposed highly accurate prediction models that have typically relied on climate parameters. However, climate factors can be unreliable and can lower the effectiveness of prediction when t...
Insect Vectors Severe Dengue Morbidity Humans Incidence Reproducibility of Results Climate Algorithms Models, Theoretical Animals Aedes Female Support Vector Machine Male Environment Dengue Virus Thailand
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