… a machine learning multi-city model of MSW generation with high accuracy. It is applied
to analyze and explore the waste management modes of two typical large cities in China. …

… (IoT), information technology, machine learning (ML) have drastically improved the efficiency
of various SWM processes, namely waste forecasting, collection, transportation, sorting and …

… This paper proposes a new architecture for a smart waste management system based on …
Learning In machine learning problems, the lack of labeled data can make supervised learning …

… It is important to adopt a smart waste management system in place to cope with a range
of waste materials. This research aims to develop a smart modelling method that could …

… in the planning, design, and implementation of solid waste management system in China. …
Thus, the machine learning model developed in this paper promotes the effective prediction …

… Principal components were used as input for traditional models (multivariable linear
regression, generalized linear model) as well as tree-based machine learning models (regression …

… is the precise knowledge in predicting the solid waste production, which, due to the high …
the most difficult tasks in waste management. Forecasting the amount of waste produced, is the …

… for optimal municipal solid waste management in the … machine learning models. First, the
optimization model determines the optimal supply chain for the municipal waste management …

… Traditional sorting of waste takes time and is prone to human mistakes. This solution uses
IoT and machine learning to overcome these restrictions and improve waste management …

… The main contribution of the present investigation is to endorse the efficiency of machine
learning and/or deep learning techniques (particularly, YOLO family) for waste segregation …