AIMC Topic: Solid Waste

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Prediction of municipal solid waste generation and analysis of dominant variables in rapidly developing cities based on machine learning - a case study of China.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA Aug 28, 2023
Prediction of municipal solid waste (MSW) generation plays an essential role in effective waste management. The main objectives of this study were to develop models for accurate prediction of MSW generation (MSWG) and analyze the influence of dominan...
China Cities Waste Management Neural Networks, Computer Population Density Machine Learning Refuse Disposal Models, Theoretical Solid Waste
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Recent advances in applications of artificial intelligence in solid waste management: A review.

Chemosphere Sep 29, 2022
Efficient management of solid waste is essential to lessen its potential health and environmental impacts. However, the current solid waste management practices encounter several challenges. The development of effective waste management systems using...
Artificial Intelligence Forecasting Reproducibility of Results Solid Waste Waste Management
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Entropy and discrimination measures based q-rung orthopair fuzzy MULTIMOORA framework for selecting solid waste disposal method.

Environmental science and pollution research international Sep 19, 2022
Fastest growing population, rapid urbanization, and growth in the disciplines of science and technology cause continually development in the amount and diversity of solid waste. In modern world, evaluation of an appropriate solid waste disposal metho...
Solid Waste Uncertainty Entropy Fuzzy Logic Refuse Disposal Decision Making
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Deep learning hybrid predictions for the amount of municipal solid waste: A case study in Shanghai.

Chemosphere Aug 20, 2022
It is crucial to precisely estimate the municipal solid waste (MSW) amount for its sustainable management. Owing to learning complicated and abstract features between the factors and target, deep learning has recently emerged as one of the useful too...
Cities Solid Waste Deep Learning China Waste Management Refuse Disposal Humans
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Pyrolytic characteristics of fine materials from municipal solid waste using TG-FTIR, Py-GC/MS, and deep learning approach: Kinetics, thermodynamics, and gaseous products distribution.

Chemosphere Jan 5, 2022
Fine materials (FM) from municipal solid waste (MSW) classification require disposal, and pyrolysis is a feasible method for the treatments. Hence, the behavior, kinetics, and products of FM pyrolysis were investigated in this study. A deep learning ...
Pyrolysis Thermogravimetry Thermodynamics Solid Waste Gases Kinetics Gas Chromatography-Mass Spectrometry Deep Learning Spectroscopy, Fourier Transform Infrared
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A European household waste management approach: Intelligently clean Ukraine.

Journal of environmental management Jun 10, 2021
The European-wide environmental obstacles of inefficient and unsustainable recycling systems and flows constrain household waste (HW) management, endangering the circular economy. The European 2020 strategy and ongoing environmental disasters indicat...
Solid Waste Waste Management Ukraine Artificial Intelligence Recycling
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Application of artificial neural networks for predicting the physical composition of municipal solid waste: An assessment of the impact of seasonal variation.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA Feb 18, 2021
Sustainable planning of waste management is contingent on reliable data on waste characteristics and their variation across the seasons owing to the consequential environmental impact of such variation. Traditional waste characterization techniques i...
Neural Networks, Computer Artificial Intelligence South Africa Seasons Solid Waste
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Variables Influencing per Capita Production, Separate Collection, and Costs of Municipal Solid Waste in the Apulia Region (Italy): An Experience of Deep Learning.

International journal of environmental research and public health Jan 17, 2021
Municipal solid waste (MSW) must be managed to reduce its impact on environmental matrices and population health as much as possible. In particular, the variables that influence the production, separate waste collection, and costs of MSW must be unde...
Italy Costs and Cost Analysis Humans Solid Waste Deep Learning Refuse Disposal Waste Management Cities
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Landfill site selection by integrating fuzzy logic, AHP, and WLC method based on multi-criteria decision analysis.

Environmental science and pollution research international Jan 6, 2021
Rapid population growth integrated with poor governance and urban planning is highly challenging resulting key for the selection of unsuitable landfill sites, particularly in developing counties. Therefore, the aim of this study is to investigate the...
Waste Disposal Facilities Solid Waste Geographic Information Systems Cities Refuse Disposal Fuzzy Logic
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Development of a Prediction Model for Demolition Waste Generation Using a Random Forest Algorithm Based on Small DataSets.

International journal of environmental research and public health Sep 24, 2020
Recently, artificial intelligence (AI) technologies have been employed to predict construction and demolition (C&D) waste generation. However, most studies have used machine learning models with continuous data input variables, applying algorithms, s...
Support Vector Machine Construction Industry Machine Learning Solid Waste Neural Networks, Computer Algorithms Artificial Intelligence
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