Applying machine learning approach in recycling
Erkınay Özdemir, Merve Ali, Zaara Subeshan, Balakrishnan Asmatulu, Eylem
Erkınay Özdemir, Merve
Ali, Zaara
Subeshan, Balakrishnan
Asmatulu, Eylem
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Issue Date
2021-02-17
Type
Article
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Keywords
Machine learning,Neural network,Decision making,Advanced recycling
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Citation
Erkinay Ozdemir, M., Ali, Z., Subeshan, B., & Asmatulu, E. (2021). Applying machine learning approach in recycling. Journal of Material Cycles and Waste Management, doi:10.1007/s10163-021-01182-y
Abstract
Waste generation has been increasing drastically based on the world’s population and economic growth. This has signifcantly
afected human health, natural life, and ecology. The utilization of limited natural resources, and the harming of the earth
in the process of mineral extraction, and waste management have far exceeded limits. The recycling rate are continuously
increasing; however, assessments show that humans will be creating more waste than ever before. Some difculties during
recycling include the signifcant expense involved during the separation of recyclable waste from non-disposable waste.
Machine learning is the utilization of artifcial intelligence (AI) that provides a framework to take as a structural improvement
of the fact without being programmed. Machine learning concentrates on the advancement of programs that can obtain the
information and use it to learn to make future decisions. The classifcation and separation of materials in a mixed recycling
application in machine learning is a division of AI that is playing an important role for better separation of complex waste.
The primary purpose of this study is to analyze AI by focusing on machine learning algorithms used in recycling systems.
This study is a compilation of the most recent developments in machine learning used in recycling industries.
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Publisher
Springer Nature
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Journal of Material Cycles and Waste Management;
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ISSN
1438-4957
1611-8227
1611-8227