Accurate prediction of domestic waste generation is a challenging task for municipalities to
implement sustainable waste management strategies. In the present study, domestic waste …

With the rapid development of industrialization and urbanization, urban sustainability has
been challenged by ever-worsening environmental problems and calls for a smart strategy …

Integrated large-scale solid waste management (SWM) policies are the need of the hour to
design, develop and sustain SWM models. An accurate prediction and forecasting of …

Municipal solid waste (MSW) management is a major concern to local governments to
protect human health, the environment and to preserve natural resources. The design and …

Municipal solid waste generation is an important parameter in waste management with
significant impacts on environment. There are many components directly influencing solid …

Predicting the mass of solid waste generation plays an important role in integrated solid
waste management plans. In this study, the performance of two predictive models, Artificial …

Abstract Machine learning (ML) algorithms, such as neural networks, random forest, and
more recent deep learning, are illustrating their utility for waste recycling. The increasing …

We propose a hybrid deep learning neural network model for accurately calculating
municipal solid waste (MSW) production and diversions with socioeconomic and …

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 …

The evolution of machine learning (ML) algorithms provides researchers and engineers with
state-of-the-art tools to dynamically model complex relationships. The design and operation …