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 …

Effective municipal solid waste management is essential for public health, environmental
protection, economic benefits, and clean energy generation for future commercial …

We present a survey of machine learning works that attempt to organize the process flow of
waste management in smart cities. Unlike past reviews, we focused on the waste generation …

Increasing generation of municipal solid waste, heterogeneity of waste composition, and
complex processes of waste management and recovery have limited the performance of …

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 …

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

The main aim of this work was to compare six machine learning (ML)-based models to
predict the municipal solid waste (MSW) generation from selected residential areas of …

Conventional treatment and recycling methods of organic solid waste contain inherent flaws,
such as low efficiency, low accuracy, high cost, and potential environmental risks. In the past …

Future projections of municipal solid waste (MSW) generation trends can resolve data
inadequacy in formulating a sustainable MSW management framework. Artificial neural …

Integrated management of municipal solid waste (MSW) is a major environmental challenge
encountered by many countries. To support waste treatment/management and national …