Automated Machine Learning in Waste Classification: A Revolutionary Approach to Efficiency and Accuracy

Z Lee, YC Wu, X Wang - Proceedings of the 2023 12th International …, 2023 - dl.acm.org
In recent years, waste segregation, treatment, and recycling have become critical global
issues, drawing significant attention worldwide. However, the efficiency of recycling …

[PDF][PDF] Forecasting of municipal solid waste generation for medium scale towns located in the state of Gujarat, India

V Patel, S Meka - International Journal of Innovative Research in Science …, 2013 - nswai.org
Rapid industrialization and population explosion has led to the migration of people from
villages to towns, which generate thousands of tons of MSW daily. One of the main functions …

[HTML][HTML] Machine learning approach for a circular economy with waste recycling in smart cities

X Chen - Energy Reports, 2022 - Elsevier
The information and communication technology (ICT) makes the smart city exchange
information with the general public and deliver higher-quality services to citizens. The …

Prediction of municipal solid waste generation using nonlinear autoregressive network

MK Younes, ZM Nopiah, NEA Basri, H Basri… - Environmental …, 2015 - Springer
Most of the developing countries have solid waste management problems. Solid waste
strategic planning requires accurate prediction of the quality and quantity of the generated …

Recycling waste classification using emperor penguin optimizer with deep learning model for bioenergy production

AI Khan, ASA Alghamdi, YB Abushark, F Alsolami… - Chemosphere, 2022 - Elsevier
The growth and implementation of biofuels and bioenergy conversion technologies play an
important part in the production of sustainable and renewable energy resources in the …

Hidden Markov model for municipal waste generation forecasting under uncertainties

P Jiang, X Liu - European Journal of Operational Research, 2016 - Elsevier
Waste generation forecasting is a complex process that is found to be influenced by some
latent influencing parameters and their uncertainties, such as economic growth …

Identification of urban sectors prone to solid waste accumulation: A machine learning approach based on social indicators

L Izquierdo-Horna, M Damazo, D Yanayaco - Computers, Environment and …, 2022 - Elsevier
In the last decades, the accumulation of municipal solid waste in urban areas has become a
latent concern in our society due to its implications for the exposed population and the …

[HTML][HTML] Forecasting of municipal solid waste multi-classification by using time-series deep learning depending on the living standard

AKA Ahmed, AM Ibraheem, MK Abd-Ellah - Results in Engineering, 2022 - Elsevier
The type and quantity of municipal solid waste are important factors for determining how
these wastes should be handled, managed, and valorised. This paper investigates the effect …

A novel domain knowledge-informed machine learning approach for modeling solid waste management systems

R He, MJ Small, IJ Scott, M Olarinre… - Environmental …, 2023 - ACS Publications
Sustainability challenges, such as solid waste management, are usually scientifically
complex and data scarce, which makes them not amenable to science-based analytical …

[HTML][HTML] Exploring Key Components of Municipal Solid Waste in Prediction of Moisture Content in Different Functional Areas Using Artificial Neural Network

T He, D Niu, G Chen, F Wu, Y Chen - Sustainability, 2022 - mdpi.com
Moisture content is a very important parameter for municipal solid waste (MSW) treatment
technology selection and design. However, the moisture content of MSW collected from …