Artificial intelligence applications in solid waste management: A systematic research review

M Abdallah, MA Talib, S Feroz, Q Nasir, H Abdalla… - Waste Management, 2020 - Elsevier
The waste management processes typically involve numerous technical, climatic,
environmental, demographic, socio-economic, and legislative parameters. Such complex …

Applying artificial neural networks (ANNs) to solve solid waste-related issues: A critical review

A Xu, H Chang, Y Xu, R Li, X Li, Y Zhao - Waste Management, 2021 - Elsevier
Artificial neural networks (ANNs) have recently attracted significant attention in
environmental areas because of their great self-learning capability and good accuracy in …

Analysis of input set characteristics and variances on k-fold cross validation for a Recurrent Neural Network model on waste disposal rate estimation

HL Vu, KTW Ng, A Richter, C An - Journal of environmental management, 2022 - Elsevier
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 …

Tackling environmental challenges in pollution controls using artificial intelligence: A review

Z Ye, J Yang, N Zhong, X Tu, J Jia, J Wang - Science of the Total …, 2020 - Elsevier
This review presents the developments in artificial intelligence technologies for
environmental pollution controls. A number of AI approaches, which start with the reliable …

Forecasting municipal solid waste generation using artificial intelligence modelling approaches

M Abbasi, A El Hanandeh - Waste management, 2016 - Elsevier
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 …

Development of machine learning-based models to forecast solid waste generation in residential areas: A case study from Vietnam

XC Nguyen, TTH Nguyen, DD La, G Kumar… - Resources …, 2021 - Elsevier
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 …

A review on prediction of municipal solid waste generation models

KA Kolekar, T Hazra, SN Chakrabarty - Procedia Environmental Sciences, 2016 - Elsevier
Abstract Development of a Municipal Solid Waste Management (MSWM) plan is a complex
process. As a foundation and prerequisite for efficient MSWM plan, quantification and …

Estimation of the generation rate of different types of plastic wastes and possible revenue recovery from informal recycling

A Kumar, SR Samadder, N Kumar, C Singh - Waste Management, 2018 - Elsevier
Plastic waste generation is an inevitable product of human activities, however its
management faces challenges in many cities. Understanding the existing patterns of plastic …

Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate: A case …

S Azadi, A Karimi-Jashni - Waste management, 2016 - Elsevier
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 …

Comparison of random forest and gradient boosting machine models for predicting demolition waste based on small datasets and categorical variables

GW Cha, HJ Moon, YC Kim - International Journal of Environmental …, 2021 - mdpi.com
Construction and demolition waste (DW) generation information has been recognized as a
tool for providing useful information for waste management. Recently, numerous …