AI Medical Compendium Topic:
Environmental Monitoring

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Supervised machine learning outperforms taxonomy-based environmental DNA metabarcoding applied to biomonitoring.

Molecular ecology resources
Biodiversity monitoring is the standard for environmental impact assessment of anthropogenic activities. Several recent studies showed that high-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) could overcome many limitations ...

Application of fuzzy logic tools for the biogeochemical characterisation of (un)contaminated waters from Aljustrel mining area (South Portugal).

Chemosphere
Aljustrel mining area (South Portugal) belongs to the Iberian Pyrite Belt (IPB). It is classified of high environmental risk due to its large tailings and to the Acid Mine Drainage (AMD) affected waters, generated by sulphides' oxidation. Integrating...

Modeling of an activated sludge process for effluent prediction-a comparative study using ANFIS and GLM regression.

Environmental monitoring and assessment
In this paper, nonlinear system identification of the activated sludge process in an industrial wastewater treatment plant was completed using adaptive neuro-fuzzy inference system (ANFIS) and generalized linear model (GLM) regression. Predictive mod...

Effect of Cd and Pb Pollutions on Physiological Growth: Wavelet Neural Network (WNN) as a New Approach on Age Determination of Coenobita scaevola.

Bulletin of environmental contamination and toxicology
Environmental pollution of aquatic ecosystems leads to an interference in several fundamental biochemical and physiological functions. In this study the interference of Cd and Pb pollutions on the physiological growth and subsequently on the age dete...

Artificial neural networks: Modeling tree survival and mortality in the Atlantic Forest biome in Brazil.

The Science of the total environment
Models to predict tree survival and mortality can help to understand vegetation dynamics and to predict effects of climate change on native forests. The objective of the present study was to use Artificial Neural Networks, based on the competition in...

Analysis of the adsorption and retention models for Cd, Cr, Cu, Ni, Pb, and Zn through neural networks: selection of variables and competitive model.

Environmental science and pollution research international
In this study, the neural networks are used to predict and explain the behavior of different edaphological variables in the adsorption and retention of heavy metals, both isolated and competing. A comparison with the results obtained using multiple r...

Research on air pollutant concentration prediction method based on self-adaptive neuro-fuzzy weighted extreme learning machine.

Environmental pollution (Barking, Essex : 1987)
In order to improve the prediction accuracy and real-time of the air pollutant concentration prediction, this paper proposes self-adaptive neuro-fuzzy weighted extreme learning machine (ANFIS-WELM) based on the weighted extreme learning machine (WELM...

A study on plant root apex morphology as a model for soft robots moving in soil.

PloS one
Plants use many strategies to move efficiently in soil, such as growth from the tip, tropic movements, and morphological changes. In this paper, we propose a method to translate morphological features of Zea mays roots into a new design of soft robot...

A bioavailable strontium isoscape for Western Europe: A machine learning approach.

PloS one
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
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...