AIMC Topic: Refuse Disposal

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Machine learning-aided unveiling the relationship between chemical pretreatment and methane production of lignocellulosic waste.

Waste management (New York, N.Y.) Jul 27, 2024
Chemical pretreatment is a common method to enhance the cumulative methane yield (CMY) of lignocellulosic waste (LW) but its effectiveness is subject to various factors, and accurate estimation of methane production of pretreated LW remains a challen...
Biofuels Refuse Disposal Machine Learning Methane Lignin
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MSW-Net: A hierarchical stacking model for automated municipal solid waste classification.

Journal of the Air & Waste Management Association (1995) Jul 15, 2024
Efficient solid waste management is crucial for urban health and welfare in the midst of fast industrialization and urbanization. In this changing environment, government authorities have a significant role in addressing and reducing the effects of s...
Neural Networks, Computer Cities Solid Waste Waste Management Refuse Disposal Models, Theoretical Bayes Theorem
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Image capturing, segmentation and data analysis of shredded refuse streams.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA Jun 23, 2024
Refuse sorting is an important cornerstone of the recycling industry, but ever-changing refuse compositions and the desire to increase recycling rates still pose many unsolved challenges. The digitalisation of refuse sorting plants promises to overco...
Neural Networks, Computer Refuse Disposal Recycling Data Analysis Solid Waste Image Processing, Computer-Assisted
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Higher heating value estimation of wastes and fuels from ultimate and proximate analysis by using artificial neural networks.

Waste management (New York, N.Y.) May 30, 2024
Higher heating value (HHV) is one of the most important parameters in determining the quality of the fuels. In this study, comparatively large datasets of ultimate and proximate analysis are constructed to be used in HHV estimation of several classes...
Refuse Disposal Waste Management Wood Neural Networks, Computer Waste Products Solid Waste Manure Animals Heating Sewage
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Identifying ESG types of Chinese solid waste disposal companies based on machine learning methods.

Journal of environmental management May 25, 2024
In the context of China's efforts to combat climate change and promote sustainable development, the solid waste treatment industry's environmental, social, and corporate governance (ESG) performance is receiving significant attention. To comprehensiv...
Machine Learning China Solid Waste Waste Management Refuse Disposal
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Artificial Intelligence in enhancing sustainable practices for infectious municipal waste classification.

Waste management (New York, N.Y.) May 11, 2024
This research paper focuses on effective infectious municipal waste management in urban settings, highlighting a dearth of dedicated research in this domain. Unlike general or specific waste types, infectious waste poses distinct health and environme...
Algorithms Neural Networks, Computer Cities Waste Management Artificial Intelligence Solid Waste Refuse Disposal
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Integrating fuzzy-AHP and GIS for solid waste disposal site selection in Kenitra province, NW Morocco.

Environmental monitoring and assessment May 10, 2024
Selecting an optimal solid waste disposal site is one of the decisive waste management issues because unsuitable sites cause serious environmental and public health problems. In Kenitra province, northwest Morocco, sustainable disposal sites have bec...
Fuzzy Logic Solid Waste Geographic Information Systems Environmental Monitoring Waste Disposal Facilities Morocco Waste Management Refuse Disposal
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Integrating advanced techniques and machine learning for landfill leachate treatment: Addressing limitations and environmental concerns.

Environmental pollution (Barking, Essex : 1987) May 9, 2024
This review article explores the challenges associated with landfill leachate resulting from the increasing disposal of municipal solid waste in landfills and open areas. The composition of landfill leachate includes antibiotics (0.001-100 μg), heavy...
Solid Waste Metals, Heavy Refuse Disposal Waste Disposal Facilities Water Pollutants, Chemical Biodegradation, Environmental Artificial Intelligence Machine Learning
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A comprehensive review on the integration of geographic information systems and artificial intelligence for landfill site selection: A systematic mapping perspective.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA Apr 23, 2024
Properly selecting landfill sites for waste disposal is crucial for mitigating environmental and public health risks. Geographic Information Systems (GISs) and Artificial Intelligence (AI) techniques have emerged as valuable tools for identifying sui...
Refuse Disposal Artificial Intelligence Waste Disposal Facilities Geographic Information Systems
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Multi-objective location-routing optimization based on machine learning for green municipal waste management.

Waste management (New York, N.Y.) Apr 12, 2024
Most of the existing municipal waste management (MWM) systems focus on the optimization of the waste disposal center locations and waste collection paths, which can be modeled based on the location-routing problem (LRP). This study models a green MWM...
Refuse Disposal Machine Learning Waste Management Algorithms Cities Beijing Models, Theoretical
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