Conference proceedings

Displaying 1 - 4 of 4 in Environmental data analysis and modelling (remove filter), neural (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

Conference:

CEST2021

Paper ID:

cest2021_00347

Comparison of regression model and artificial neural network model in noise prediction in a mixed area of Dhaka City

(Corresponding) Chowdhury V., Zarif S., Tofa T., Laskar M.

Topic:

Environmental data analysis and modelling

The equivalent noise levels regularly exceed acceptable limits within Dhaka city, the capital of Bangladesh, especially in the mixed urban areas (where trips are generated to serve commercial, residential, and industrial demands). The study aims to assess the noise level in mixed urban areas, build...Read more

Keywords:

Noise pollution, Equivalent noise level, Prediction model, Regression, Artificial Neural Network.

DOI:

https://doi.org/10.30955/gnc2021.00482

Conference:

CEST2021

Paper ID:

cest2021_00482

Nonlinear Autoregressive Neural Networks for Air Temperature forecasting

Philippopoulos K., (Corresponding) Tzanis C., Deligiorgi D., Alimissis A.

Topic:

Environmental data analysis and modelling

In the field of climatic conditions forecasting, the linear classical time series models are inadequate for modelling and predicting accurately the air temperature variability. This work presents the novel application of nonlinear autoregressive neural networks (NAR) in air temperature forecasting...Read more

Keywords:

Air temperature, Machine Learning, Artificial Neural Networks, Dynamic Neural Networks, Forecasting

DOI:

https://doi.org/10.30955/gnc2021.00485

Conference:

CEST2021

Paper ID:

cest2021_00485

A Deep Learning Model, interpreted with an XAI technique, to simulate and optimize the remediation of oil-drilling cuttings in bubble flow reactors

Kalari K., Christodoulis K., Bali N., Theodoropoulou M., (Corresponding) Tsakiroglou C.

Topic:

Environmental data analysis and modelling

A multitask deep neural network (DNN) is developed to simulate the ozonation of oil-drilling cuttings (ODC) and is interpreted through a technique of explainable artificial intelligence (XAI) to provide knowledge about the experimental conditions that will maximize the decontamination of ODC. On a...Read more

Keywords:

Ozonation, Soil Remediation, Bubble Column Reactor, Deep Neural Networks, Multitask Learning, Explainable Artificial Intelligence.

DOI:

https://doi.org/10.30955/gnc2023.00166

Conference:

CEST2023

Paper ID:

cest2023_00166