Conference proceedings

Displaying 1 - 2 of 2 in CEST2021 (remove filter), Environmental data analysis and modelling (remove filter), predictions (remove filter)

CEST Proceedings are published under the ISSN 2944-9820.

Artificial Neural Network (ANNs) for predicting petroleum hydrocarbons from heavy metals contaminated soils around fuel stations

(Corresponding) Bonelli M., Manni A., Saviano G.

Topic:

Environmental data analysis and modelling

Petrol stations are classified as a dangerous source of pollution for the human population due to the toxicity of emissions from evaporated vehicle fuels and fuel spillages. The contaminants released in the environment are mainly complex mixtures of petroleum hydrocarbon compounds (PHCs) and heavy...Read more

Keywords:

Artificial Neural Network predictions, heavy metals, field portable XRF, petroleum hydrocarbon compounds

DOI:

https://doi.org/10.30955/gnc2021.00347

Paper ID:

cest2021_00347

A data-driven approach to predict phytoplankton blooms using satellite-derived water quality and hydrometeorological drivers

(Corresponding) Kandris K., Romas E., Tzimas A., Bresciani M., Giardino C., Bauer P., Pechlivanidis I., Dessena M.

Topic:

Environmental data analysis and modelling

The present work leverages simulated hydrometeorological factors and satellite-derived chlorophyll-a to predict phytoplankton dynamics for Mulargia reservoir (Sardinia, Italy). A Random Forest (RF) model was (a) calibrated to minimize out-of-bag errors of chlorophyll-a predictions for a 5-year-long...Read more

Keywords:

Machine learning; forecasting; phytoplankton blooms; remote sensing; hydrometeorological predictions

DOI:

https://doi.org/10.30955/gnc2021.00420

Paper ID:

cest2021_00420