AIMC Topic: Atmosphere
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Forecasting of bioaerosol concentration by a Back Propagation neural network model.
The Science of the total environment
Sep 5, 2019
Bioaerosol in the atmosphere plays a very important role in environment and public health. To forecast the bioaerosol concentration, the correlation between bioaerosol concentration and meteorological factors was discussed, and a Back Propagation (BP...
Estimating the daily pollen concentration in the atmosphere using machine learning and NEXRAD weather radar data.
Environmental monitoring and assessment
Jun 7, 2019
Millions of people have an allergic reaction to pollen. The impact of pollen allergies is on the rise due to increased pollen levels caused by global warming and the spread of highly invasive weeds. The production, release, and dispersal of pollen de...
Forecasting the spatiotemporal variability of soil CO emissions in sugarcane areas in southeastern Brazil using artificial neural networks.
Environmental monitoring and assessment
Nov 21, 2018
Carbon dioxide (CO) is considered one of the main greenhouse effect gases and contributes significantly to global climate change. In Brazil, the agricultural areas offer an opportunity to mitigate this effect, especially with the sugarcane crop, sinc...
Estimating regional effects of climate change and altered land use on biosphere carbon fluxes using distributed time delay neural networks with Bayesian regularized learning.
Neural networks : the official journal of the International Neural Network Society
Aug 16, 2018
The ability to accurately predict changes of the carbon and energy balance on a regional scale is of great importance for assessing the effect of land use changes on carbon sequestration under future climate conditions. Here, a suite of land cover-sp...
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...
Anthropogenic activities impact on atmospheric environmental quality in a gas-flaring community: application of fuzzy logic modelling concept.
Environmental science and pollution research international
May 24, 2018
We present a modelling concept for evaluating the impacts of anthropogenic activities suspected to be from gas flaring on the quality of the atmosphere using domestic roof-harvested rainwater (DRHRW) as indicator. We analysed seven metals (Cu, Cd, Pb...
A modified artificial neural network based prediction technique for tropospheric radio refractivity.
PloS one
Mar 1, 2018
Radio refractivity plays a significant role in the development and design of radio systems for attaining the best level of performance. Refractivity in the troposphere is one of the features affecting electromagnetic waves, and hence the communicatio...
Co-combustion of sewage sludge and coffee grounds under increased O/CO atmospheres: Thermodynamic characteristics, kinetics and artificial neural network modeling.
Bioresource technology
Nov 13, 2017
(Co-)combustion characteristics of sewage sludge (SS), coffee grounds (CG) and their blends were quantified under increased O/CO atmosphere (21, 30, 40 and 60%) using a thermogravimetric analysis. Observed percentages of CG mass loss and its maximum ...
A Neural Network Model for K(λ) Retrieval and Application to Global Kpar Monitoring.
PloS one
Jun 17, 2015
Accurate estimation of diffuse attenuation coefficients in the visible wavelengths Kd(λ) from remotely sensed data is particularly challenging in global oceanic and coastal waters. The objectives of the present study are to evaluate the applicability...
Input strategy analysis for an air quality data modelling procedure at a local scale based on neural network.
Environmental monitoring and assessment
Apr 30, 2015
In recent years, a significant part of the studies on air pollutants has been devoted to improve statistical techniques for forecasting the values of their concentrations in the atmosphere. Reliable predictions of pollutant trends are essential not o...
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