AIMC Topic: Refuse Disposal

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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...
Humans Italy Costs and Cost Analysis Solid Waste Deep Learning Cities Waste Management Refuse Disposal
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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...
Fuzzy Logic Solid Waste Waste Disposal Facilities Refuse Disposal Geographic Information Systems Cities
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A multi-attribute decision-making-based site selection assessment algorithm for garbage disposal plant using interval q-rung orthopair fuzzy power Muirhead mean operator.

Environmental research Nov 7, 2020
With the increase of the global population and the improvement of people's living standards, the output of garbage generated by human activities is also increasing day by day. Choosing an appropriate garbage disposal site is one of the key links for ...
Refuse Disposal Decision Making Uncertainty Humans Algorithms Fuzzy Logic
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A comparison of fuzzy logic and TOPSIS methods for landfill site selection according to field visits, engineering geology approach and geotechnical experiments (case study: Rudbar County, Iran).

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA Sep 16, 2020
The present study evaluated and selected the best location among susceptible landfill sites in Rudbar County using 27 criteria, as the maximum effective criteria, in the decision-making process. The emergence and comparison between the two methods of...
Waste Disposal Facilities Geology Refuse Disposal Fuzzy Logic Iran
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Interpretable machine learning for predicting biomethane production in industrial-scale anaerobic co-digestion.

The Science of the total environment Dec 23, 2019
The objective of this study is to apply machine learning models to accurately predict daily biomethane production in an industrial-scale co-digestion facility. The methodology involved applying elasticnet, random forest, and extreme gradient boosting...
Machine Learning Anaerobiosis Food Refuse Disposal Methane
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An Integrated Fuzzy AHP and Fuzzy TOPSIS Approach to Assess Sustainable Urban Development in an Emerging Economy.

International journal of environmental research and public health Aug 13, 2019
Sustainable urban development (SUD) requires a balance between economic growth, social well-being, and environmental protection. Oftentimes, urban policy makers can hardly fulfill all SUD goals due to inadequacy of resources to support SUD programs. ...
Humans Urbanization Sustainable Development Fuzzy Logic Refuse Disposal Conservation of Natural Resources
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Innovation hotspots in food waste treatment, biogas, and anaerobic digestion technology: A natural language processing approach.

The Science of the total environment Apr 7, 2019
The objective of this study is to apply natural language processing to identifying innovative technology trends related to food waste treatment, biogas, and anaerobic digestion. The methodology used involved analyzing large volumes of text data mined...
Food Refuse Disposal Bioreactors Biofuels Anaerobiosis Methane Natural Language Processing
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Prediction of municipal solid waste generation using artificial neural network approach enhanced by structural break analysis.

Environmental science and pollution research international Oct 7, 2016
This paper presents the development of a general regression neural network (GRNN) model for the prediction of annual municipal solid waste (MSW) generation at the national level for 44 countries of different size, population and economic development ...
Models, Theoretical Developing Countries Neural Networks, Computer Forecasting Refuse Disposal Solid Waste Developed Countries Waste Management
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How to improve WEEE management? Novel approach in mobile collection with application of artificial intelligence.

Waste management (New York, N.Y.) Mar 2, 2016
In global demand of improvement of electrical and electronic waste management systems, stakeholders look for effective collection systems that generate minimal costs. In this study we propose a novel model for application in mobile collection schemes...
Recycling Cities Artificial Intelligence Electronic Waste Models, Theoretical Poland Waste Management Refuse Disposal
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Plastics detection and sorting using hyperspectral sensing and machine learning algorithms.

Waste management (New York, N.Y.) Jul 15, 2025
Plastic waste second life management requires effective detection (and sorting if necessary) techniques to tackle the environmental challenge it poses. This research explores the application of hyperspectral imaging in the spectral range 900-1700 nm ...
Remote Sensing Technology Plastics Algorithms Principal Component Analysis Recycling Waste Management Refuse Disposal Discriminant Analysis Hyperspectral Imaging Machine Learning
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