AI Medical Compendium Journal:
Ecotoxicology and environmental safety

Showing 41 to 50 of 52 articles

Estimating PM concentration using the machine learning GA-SVM method to improve the land use regression model in Shaanxi, China.

Ecotoxicology and environmental safety
With rapid economic growth, urbanization and industrialization, fine particulate matter with aerodynamic diameters ≤ 2.5 µm (PM) has become a major pollutant and shows adverse effects on both human health and the atmospheric environment. Many studies...

Predicting the consequences of accidents involving dangerous substances using machine learning.

Ecotoxicology and environmental safety
A new dimension of learning lessons from the occurrence of hazardous events involving dangerous substances is considered relying on the availability of representative data and the significant evolution of a wide range of machine learning tools. The i...

A novel soft sensor based warning system for hazardous ground-level ozone using advanced damped least squares neural network.

Ecotoxicology and environmental safety
Estimation of hazardous air pollutants in the urban environment for maintaining public safety is a significant concern to mankind. In this paper, we have developed an efficient air quality warning system based on a low-cost and robust ground-level oz...

Predicting the concentration of total coliforms in treated rural domestic wastewater by multi-soil-layering (MSL) technology using artificial neural networks.

Ecotoxicology and environmental safety
Many indicators are involved in monitoring water quality. For instance, the fecal indicator bacteria are extremely important to detect the water quality. For this purpose, to better predict the total coliforms at the outlet of a Multi-Soil-Layering (...

Manganese (Mn) removal prediction using extreme gradient model.

Ecotoxicology and environmental safety
Exploring the Manganese (Mn) removal prediction with several independent variables is tremendously critical and indispensable to understand the pattern of removal process. Mn is one of the key heavy metals (HMs) stipulated by the WHO for the developm...

Artificial intelligence models to predict acute phytotoxicity in petroleum contaminated soils.

Ecotoxicology and environmental safety
Environment pollutants, especially those from total petroleum hydrocarbons (TPH), have a highly complex chemical, biological and physical impact on soils. Here we study this influence via modelling the TPH acute phytotoxicity effects on eleven sample...

Effects of corn straw on dissipation of polycyclic aromatic hydrocarbons and potential application of backpropagation artificial neural network prediction model for PAHs bioremediation.

Ecotoxicology and environmental safety
In order to provide a viable option for remediation of PAHs-contaminated soils, a greenhouse experiment was conducted to assess the effect of corn straw amendment (1%, 2%, 4% or 6%, w/w) on dissipation of aged polycyclic aromatic hydrocarbons (PAHs) ...

Evaluating genotoxicity of metal oxide nanoparticles: Application of advanced supervised and unsupervised machine learning techniques.

Ecotoxicology and environmental safety
Presence of missing data points in datasets is among main challenges in handling the toxicological data for nanomaterials. As the processing of missing data is an important part of data analysis, we have introduced a read-across approach that uses a ...

Machine vision analysis on abnormal respiratory conditions of mice inhaling particles containing cadmium.

Ecotoxicology and environmental safety
Inhalable environmental toxicants can induce pulmonary malfunction resulting abnormal respiratory conditions. The traditional methods currently available to detect the respiratory condition of animals rely on differential pressure transducers and sig...

Sequential prediction of quantitative health risk assessment for the fine particulate matter in an underground facility using deep recurrent neural networks.

Ecotoxicology and environmental safety
Particulate matter with aerodynamic diameter less than 2.5 µm (PM) in indoor public spaces such as subway stations, has represented a major public health concern; however, forecasting future sequences of quantitative health risk is an effective metho...