Optimizing waste-to-energy conversion: Unveiling the potential of unsupervised clustering through the new HOM classification system-Reference-Cited by-同舟云学术

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Optimizing waste-to-energy conversion: Unveiling the potential of unsupervised clustering through the new HOM classification system

Published:2024-05 Issue: Volume:65 Page:103796
ISSN:2213-1388
Container-title:Sustainable Energy Technologies and Assessments
language:en
Short-container-title:Sustainable Energy Technologies and Assessments

Author:

Insel Mert Akin,Yucel Ozgun^ORCID,Sadikoglu Hasan

Publisher

Elsevier BV

Reference56 articles.

1. Short review on the origin and countermeasure of biomass slagging in grate furnace;Zhu;Front Energy Res,2014

2. Classification of solid fuels with machine learning;Elmaz;Fuel,2020

3. Soft Independent Modelling of Class Analogy applied to infrared spectroscopy for rapid discrimination between hardwood and softwood;Duca;Energy,2016

4. Energy Efficiency and Greenhouse Gas Emission Intensity of Petroleum Products at U.S. Refineries;Elgowainy;Environ Sci Technol,2014

5. Metrics for energy performance in operation: the fallacy of single indicators;Bordass;Buildings and Cities,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A state-of-the-art review on machine learning based municipal waste to energy system;Cleaner Energy Systems;2024-12

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