AIMC Topic: Environmental Monitoring

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Using wavelet-feedforward neural networks to improve air pollution forecasting in urban environments.

Environmental monitoring and assessment
The paper presents the screening of various feedforward neural networks (FANN) and wavelet-feedforward neural networks (WFANN) applied to time series of ground-level ozone (O3), nitrogen dioxide (NO2), and particulate matter (PM10 and PM2.5 fractions...

Video-tracking of zebrafish (Danio rerio) as a biological early warning system using two distinct artificial neural networks: Probabilistic neural network (PNN) and self-organizing map (SOM).

Aquatic toxicology (Amsterdam, Netherlands)
Biological early warning systems (BEWS) are becoming very important tools in ecotoxicological studies because they can detect changes in the behavior of organisms exposed to toxic substances. In this work, a video tracking system was fully developed ...

A Neural Network Model for K(λ) Retrieval and Application to Global Kpar Monitoring.

PloS one
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...

A BHR Composite Network-Based Visualization Method for Deformation Risk Level of Underground Space.

PloS one
This study proposes a visualization processing method for the deformation risk level of underground space. The proposed method is based on a BP-Hopfield-RGB (BHR) composite network. Complex environmental factors are integrated in the BP neural networ...

Evaluation of wavelet performance via an ANN-based electrical conductivity prediction model.

Environmental monitoring and assessment
The prediction of water quality parameters plays an important role in water resources and environmental systems. The use of electrical conductivity (EC) as a water quality indicator is one of the important parameters for estimating the amount of mine...

On-water remote monitoring robotic system for estimating the patch coverage of Anabaena sp. filaments in shallow water.

Environmental science. Processes & impacts
An on-water remote monitoring robotic system was developed for indirectly estimating the relative density of marine cyanobacteria blooms at the subtidal sandy-rocky beach in Balandra Cove, Baja California Sur, Mexico. The system is based on an unmann...

Input strategy analysis for an air quality data modelling procedure at a local scale based on neural network.

Environmental monitoring and assessment
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...

The use of diagnostic ratios, biomarkers and 3-way Kohonen neural networks to monitor the temporal evolution of oil spills.

Marine pollution bulletin
Oil spill identification relies usually on a wealth of chromatographic data which requires advanced data treatment (chemometrics). A simple approach based on Kohonen neural networks to handle three-dimensional arrays is presented. A suite of 28 diagn...

Selection of Atmospheric Environmental Monitoring Sites based on Geographic Parameters Extraction of GIS and Fuzzy Matter-Element Analysis.

PloS one
To effectively monitor the atmospheric quality of small-scale areas, it is necessary to optimize the locations of the monitoring sites. This study combined geographic parameters extraction by GIS with fuzzy matter-element analysis. Geographic coordin...