The waste management processes typically involve numerous technical, climatic,
environmental, demographic, socio-economic, and legislative parameters. Such complex …

Population growth and the acceleration of urbanization have led to a sharp increase in
municipal solid waste production, and researchers have sought to use advanced technology …

The use of machine learning techniques in waste management studies is increasingly
popular. Recent literature suggests k-fold cross validation may reduce input dataset partition …

Artificial neural networks (ANNs) have recently attracted significant attention in
environmental areas because of their great self-learning capability and good accuracy in …

Hazardous healthcare waste (HCW) management system is one of the most critical urban
systems affected by the COVID-19 pandemic due to the increase in waste generation rate in …

Forecasting household waste generation using traditional methods is particularly
challenging due to its high variability and uncertainty. Unlike studies that forecast waste …

Waste management has become a significant issue in most developing countries. Municipal
solid waste generation has been steadily increasing over the past decade. Recycling is …

Municipal solid waste (MSW) generation forecasting has become an important tool for
decision-making in urban environments, not only due to its essential role in effective waste …

Reliable prediction of municipal solid waste (MSW) generation rates is a significant element
of planning and implementation of sustainable solid waste management strategies. In this …

Recently, digital transformation is supposed to affect all aspects of human life profoundly.
Nevertheless, there is a lack of summaries map digital transformation in the environmental …