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Soil Pollutants, Radioactive

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Advantages of Synthetic Noise and Machine Learning for Analyzing Radioecological Data Sets.

PloS one
The ecological effects of accidental or malicious radioactive contamination are insufficiently understood because of the hazards and difficulties associated with conducting studies in radioactively-polluted areas. Data sets from severely contaminated...

Automated anomalous behaviour detection in soil radon gas prior to earthquakes using computational intelligence techniques.

Journal of environmental radioactivity
In this article, three computational intelligence (CI) models were developed to automatically detect anomalous behaviour in soil radon gas (Rn) time series data. Data were obtained at a fault line and analysed using three machine learning techniques ...

Estimation of radon flux spatial distribution in Rize, Turkey by the artificial neural networks method.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
In this study, average radon flux distribution in the Rize province (Turkey) was estimated by the artificial neural networks (ANN) method. For this purpose, terrestrial gamma dose rate (TGDR), which is defined as an important proxy in determining rad...

DEVELOPMENT OF A ROBOT FOR THE MEASUREMENT OF RADIOACTIVE CONTAMINATION AND FERTILITY OF THE SOIL IN FARMLAND.

Radiation protection dosimetry
A tractor-based robot with the capability of real-time assessing and visualizing the radioactive material density and fertility distribution of farmlands has been developed to accelerate the recovery process of the farmlands suffered by the accident ...

Radiological characterization of the tailings of an abandoned copper mine using a neural network and geostatistical analysis through the Co-Kriging method.

Environmental geochemistry and health
The radiological characterization of soil contaminated with natural radionuclides enables the classification of the area under investigation, the optimization of laboratory measurements, and informed decision-making on potential site remediation. Neu...

Developing a machine learning-based predictive model for cesium sorption distribution coefficient on crushed granite.

Journal of environmental radioactivity
The sorption of radionuclides on granite has been extensively studied over the past few decades due to its significance in the safety assessment of geological disposal for high-level radioactive waste (HLW). The sorption properties of granite for rad...