Artificial neural networks (ANNs) are suitable for modeling solid waste generation. In the
present study, four training functions, including resilient backpropagation (RP), scale …

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 …

Solid Waste (SW) is one of the critical challenges of urban life. These SWs are considered
environmental pollutants that are a threat to ecology and human health. Predicting SW …

Developing successful municipal waste management planning strategies is crucial for
implementing sustainable development. The research proposed the application of an …

Accurate prediction of municipal solid waste's quality and quantity is crucial for designing
and programming municipal solid waste management system. But predicting the amount of …

Accurate prediction of municipal solid waste generation has an important role in future
planning and waste management system. The characteristics of the generated solid waste …

Background: Municipal solid waste (MSW) is the natural result of human activities. MSW
generation modeling is of prime importance in designing and programming municipal solid …

As one of the most popular non-linear models, artificial neural network (ANN) has been
successfully applied in the prediction of municipal solid waste (MSW). Despite its high …

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

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 …