AIMC Topic: Incineration

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

Waste management (New York, N.Y.) Jan 13, 2025
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...
Machine Learning Algorithms Neural Networks, Computer Refuse Disposal Incineration Image Processing, Computer-Assisted Solid Waste
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Novel method for predicting concentrations of incineration flue gas based on waste composition and machine learning.

Journal of environmental management Dec 5, 2024
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 ...
Incineration Machine Learning Air Pollutants Solid Waste Gases
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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 Jul 30, 2024
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...
Environmental Monitoring Air Pollutants Neural Networks, Computer Nitrogen Oxides Solid Waste Incineration
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Artificial intelligence-based forecasting model for incinerator in sulfur recovery units to predict SO emissions.

Environmental research Feb 5, 2024
Pollutant emissions from chemical plants are a major concern in the context of environmental safety. A reliable emission forecasting model can provide important information for optimizing the process and improving the environmental performance. In th...
Sulfur Incineration Air Pollutants Sulfur Dioxide Machine Learning Forecasting Models, Theoretical Environmental Monitoring Neural Networks, Computer Artificial Intelligence
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Waste-to-energy incineration site selection framework based on heterogeneous fuzzy regret-PROMETHEE model considering life-cycle carbon emissions.

Environmental science and pollution research international Dec 13, 2023
Waste incineration technology has received extensive attention for its advantages of being harmless, reducing, and recycling. However, the waste-to-energy incineration project confronts significant "not-in-my-backyard (NIMBY) concerns," and irrationa...
Incineration Emotions Carbon Fuzzy Logic Decision Making Uncertainty
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Hybrid model of a cement rotary kiln using an improved attention-based recurrent neural network.

ISA transactions Feb 15, 2022
A rotary kiln is core equipment in cement calcination. Significant time delay, time-varying, and nonlinear characteristics cause challenges in the advance process control and operational optimization of the rotary kiln. However, the traditional mecha...
Incineration Neural Networks, Computer
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Assessment of medical waste generation, associated environmental impact, and management issues after the outbreak of COVID-19: A case study of the Hubei Province in China.

PloS one Jan 24, 2022
COVID-19 greatly challenges the human health sector, and has resulted in a large amount of medical waste that poses various potential threats to the environment. In this study, we compiled relevant data released by official agencies and the media, an...
Waste Management Gases Chlorides Environment Medical Waste Incineration Humans Environmental Pollution Neural Networks, Computer Air Pollution SARS-CoV-2 COVID-19 China Wastewater
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Fault Detection in the MSW Incineration Process Using Stochastic Configuration Networks and Case-Based Reasoning.

Sensors (Basel, Switzerland) Nov 5, 2021
Fault detection in the waste incineration process depends on high-temperature image observation and the experience of field maintenance personnel, which is inefficient and can easily cause misjudgment of the fault. In this paper, a fault detection me...
Neural Networks, Computer Incineration Support Vector Machine
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Comparison of ANN (MLP), ANFIS, SVM, and RF models for the online classification of heating value of burning municipal solid waste in circulating fluidized bed incinerators.

Waste management (New York, N.Y.) Apr 10, 2017
The heating values, particularly lower heating values of burning municipal solid waste are critically important parameters in operating circulating fluidized bed incineration systems. However, the heating values change widely and frequently, while th...
Solid Waste Incineration Support Vector Machine Neural Networks, Computer Heating
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