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Solid Waste

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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
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...

Soft sensing of NOx emission from waste incineration process based on data de-noising and bidirectional long short-term memory neural networks.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Continuous emission monitoring system is commonly employed to monitor NOx emissions in municipal solid waste incineration (MSWI) processes. However, it still encounters the challenges of regular maintenance and measurement lag. These issues significa...

MSW-Net: A hierarchical stacking model for automated municipal solid waste classification.

Journal of the Air & Waste Management Association (1995)
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...

Exploring artificial intelligence role in improving service building engagement in sorting.

Waste management (New York, N.Y.)
Waste management researchers have identified that the correct disposal of solid waste is better addressed upstream, where people properly sort their solid waste. Sorting solid waste is a practice that requires a behaviour friendly to sorting and will...

Co-firing characteristic prediction of solid waste and coal for supercritical CO power cycle based on CFD simulation and machine learning algorithm.

Waste management (New York, N.Y.)
The co-firing technology of combustible solid waste (CSW) and coal in the supercritical CO (S-CO) circulating fluidized bed (CFB) can effectively deal with domestic waste, promote social and environmental benefits, improve the coal conversion rate, a...

Efficient High Heating Value estimation using Latin Hypercube Sampling and Artificial Neural Network-based approach.

Environmental monitoring and assessment
To maximize energy recovery in waste-to-energy (WTE) systems, the High Heating Value (HHV) of municipal solid waste (MSW) must be accurately estimated. To forecast the HHV of MSW, this study proposes a unique method that combines an Artificial Neural...

Novel method for predicting concentrations of incineration flue gas based on waste composition and machine learning.

Journal of environmental management
The complex composition of solid waste leads to the variability of flue gas emissions during its incineration, which poses a challenge to the stable operation of incineration and pollution control systems. To address this problem, the study explored ...

Identification and information acquisition of high-value construction solid waste combined millimeter-wave radar and convolutional neural networks.

Waste management (New York, N.Y.)
The accumulation of construction solid waste (CSW) leads to the waste of land resources and environmental pollution, becoming a significant social problem. Identifying the amount of high-value CSW is essential for assessing the value of accumulated C...

Machine learning-assisted assessment of municipal solid waste thermal treatment efficacy via rapid image recognition and visual analysis.

Waste management (New York, N.Y.)
Decentralized thermal treatment is a common method for municipal solid waste (MSW) disposal in rural areas. However, evaluating the effect of incineration has always been challenging owing to the difficult and time-consuming measurements involved. He...

Enhancing door-to-door waste collection forecasting through ML.

Waste management (New York, N.Y.)
We explore the application of machine learning (ML) techniques to forecast door-to-door waste collection, addressing the challenges in municipal solid waste (MSW) management. ML models offer a promising solution to optimize waste collection operation...